For those who would like to know the total and active parameter count of this model: even though Google doesn't disclose the model technicals, we can infer them within relatively tight margins based on what we do know.
We know they serve the model on TPU 8i, which we have plenty of hard specs for (so we know the key constraints: total memory and bandwidth and compute flops). We can also set a ceiling on the compute complexity and memory demand of the model based on knowing they will be at least as efficient as what is disclosed in the Deepseek V4 Technical Report.
We can also assume that the model was explicitly built to run efficiently in a RadixAttention style batched serving scenario on a single TPU 8i (so no tensor parallelism, etc. to avoid unnecessary overheads... Google explicitly designed the 8th-generation inference architecture to eliminate the need for tensor sharding on mid-sized models).
We know Google intends to serve this model at a floor speed of around 280 tok/s too.
Putting all these pieces together, we can confidently say this model is ~250-300B total, and 10-16B active parameters. Likely mostly FP4 with FP8 where it matters most.
I do model serving optimization work. This is napkin math.
Edit: There's one factor I under-rated in my initial estimate... TurboQuant. This is a compute to KV memory use tradeoff. It's plausible with TurboQuant at a quality-neutral setting they've gotten the model up to 400B with similar economics. This is a variable effecting concurrency and the the way they decided total model size was likely based on what they see for the average user's average KV cache depth in real-world usage.
Am I really so old that when someone says "Flash" my immediate response is... "consider HTML5 instead" ??
show comments
gertlabs
Taking into account that this is a flash model, it's a strong release. It's very fast and frontier-ish for the price.
Raw intelligence is high for a flash model. But Google's problem has always been productization and tool use, whereas raw intelligence is always competitive. It does not look like they solved that with this release -- in fact, their tool use delta (the improvement in scores when given arbitrary tools and a harness) has actually regressed from some previous models.
I have google ai pro plan and tried antigravity with 3.5 flash but it used up all my quota in two prompts. If that is not a bug then it is seriously unusable.
(Switch to the cost vs performance chart to see how far this is off the Pareto frontier)
margorczynski
Wow at the price hike. Still I think in the long run the Chinese will win if they're able to produce hardware comparable to Nvidia.
show comments
wg0
3x price increase for a similar model almost. And they said AI would be cheaper and ubiquitous.
show comments
AgentMasterRace
Gemini 3.1 probation is literally the worst AI when I cycle from opus to got 5.5 then finally Gemini. It's actually insane that it's a frontier model. I rage at it more than my wife.
brikym
How is this progress? The token cost just keeps going up and up. Flash is the new Pro? Do the models actually cost more to run or is it fattening margins?
nikhilpareek13
worth noting that Google marked this stable rather than preview, which is unusual compared to their recent releases. Pair that with the 3x price hike and flash pricing now reads like long-term floor they want, not a temporary thing they will walk back later. But its hard to tell yet whether that's Google specifically reading the room or the whole industry quietly resetting the cheap-inference baseline.
ElenaDaibunny
but latency in real GUI workflows with 50+ steps is still the elephant in the room for cloud-based agents
stared
China: we don’t need to use US models, we can distill them ourself
Google: we don’t need Chinese to distill our models, we can do it ourself
paol_taja
That pelican looks like it just sold a SaaS company and bought a bike because its therapist said it needed balance.
show comments
razodactyl
Aw. The listen to article widget doesn't work properly on mobile Safari and when using the options button, the popup appears below the "In this article" dropdown occluding it.
At least it read the authors of the article to me.
I wish we would push more towards testing code. Agentic AI excel when it's engaged.
Alifatisk
The demo of the model in Antigravity automatically rename and categorize unstructured assets using vision was quite cool, it demodulates that the IDE sidepanel can be used for more than just coding. I wonder if the harness in Antigravity is based on Gemini cli or if they are completely different. Could Gemini cli do the same task? Or is the vision feature a Antigravity thing?
show comments
sbinnee
While I am excited, the price compared to gemini 3 flash preview which I used for the longest time is x3 more. Upon arrival of deepseek v4 flash, I am a happy user of deepseek. We will see how long that reign would last after I try this new gemini.
sigbeta
I am interested to see how they will serve demand with they TPU monopoly have.
mchusma
I have thought about this and I think overall, this was a disappointing release from Google. I'm not sure the sentiment, but this feels like a miss.
What they did do in the keynote was spend a lot of time talking about their distribution advantage, and how they can own the consumer in search. But not a lot that will benefit partners or developers.
Basically, they released something broadly competitive with Sonnet 4.6, a new Omni model that seems interesting but unclear yet. They have completely ceded the frontier to OpenAI / Anthropic, and are saying "look for pro next month".
The best release since nano banana pro from Google has been Gemma.
jonnyasmar
The $1.50/$9.00 pricing is a meaningful shift if you've been running Gemini as the "fast iteration" half of a multi-model coding workflow. I've had Claude Code, Codex, and Gemini CLI running side by side and the working split was "Gemini for quick scaffolding and exploration where the cost of being wrong is low, Sonnet for correctness-critical stuff." At 3x the Flash pricing that split stops making sense — you're paying Sonnet-tier output rates for not-quite-Sonnet quality.
For pure chat that's annoying but tolerable. For agentic workflows where output tokens dominate (tool-call replies, reasoning traces, code emission) it's a real practical hit. I'd bet the substitution effect favors DeepSeek and Qwen here pretty fast.
show comments
bredren
Can anyone who has extensive, recent, experience with Claude code and Codex contextualize the current Gemini CLI product experience?
show comments
pqdbr
In my tests, in real production use cases, it's a hard pass.
It's actually 10-15% slower and also more expensive than Gemini 3.1 Pro, because it thinks more than 2.5x Gemini 3.1 Pro.
So that thinking verbosity nullifies the speed and cost gains.
AND the quality is worse than 3.1 Pro for our use cases, making mistakes Pro doesn't make.
paperwork360
Google also updated Antigravity. version 2.0 is more for conversation with agent. The previous VS Code like IDE was much better.
show comments
ErystelaThevale
Gemini has been too agreeable to be useful for actual debate. Curious if 3.5 changes that, or just the benchmarks
MASNeo
Well, available for Gemini means these days that half the time they are “Receiving a lot of requests right now.” and so sorry they couldn’t complete the task. Luckily the model supports long time horizons because that’s what’s needed. /me likes Gemini a lot just wishing Google would add the compute!
show comments
x3cca
I'm excited for the conversation to switch from intelligence to tps instead. I care much less about what hard thought experiments models can one shot and much more how responsive my plain text interface for doing things is.
mackross
The antigravity teamwork-preview doesn't work for me -- upgraded to ultra, installed antigravity 2, ran teamwork-preview, keeps failing: "You have exhausted your capacity on this model. Your quota will reset after 0s."
amelius
Gemini, please block all ads in my search engine.
swe_dima
Flash family but costs like a Pro. $9 vs $12 for output.
victor9000
There was a brief moment in time where Gemini was the greatest thing since sliced bread, then it got nerfed from outer space without a version bump or any meaningful mention from Google, no thanks.
ai_fry_ur_brain
Imagine reducing yourself to the worst of averages by making your competency 1:1 correlated to the tokens that you have access too (and everyone else does).
kristopolous
I have a tool to track these I've built
Relatively speaking here's where it's at:
score age size name
44.2 97 large GLM-5 (Reasoning)
44.7 187 - GPT-5.1 (high)
44.9 29 - Qwen3.6 Max Preview
45 0 - Gemini 3.5 Flash
45.5 27 large MiMo-V2.5-Pro
45.6 75 - GPT-5.4 (low)
I really don't know why people down vote me. What do I need to say to make things for free that people like? Sincere question. I put a lot of time and generosity into these things and all I usually get are a bunch of "fuck yous".
This is honestly an existential issue for me. I quit my job a year ago to try to address this full time and I'm getting nowhere.
show comments
uean
I have to admit that 3.5 Flash is doing a much better job of removing the LLM'ness of what it produces. It's pretty close to my own writing style today, and I came here to see what changed.
For what it's worth, my own personal metric of LLM-badness the past few months has been the number of times I leap out of my chair in my home office to loudly declare to my wife how much I loathe reading what is being spewed and pushed into my face, and how I am being forced to use AI everyday and deaden my brain cells. Today is like a breath of fresh air.
owentbrown
Has anyone switched from Claude 4.7 Opus or ChatGPT 5.5 to this?
How does it feel? Dumber? Worth it for the speed? I'd love someone's subjective take on it, after doing a long session of coding.
Reiner Pope gave a talk on Dwarkesh Patel about token economics. I guess faster is a lot more expensive, generally.
Someone should make a harness that uses a fast model to keep you in-flow and speed run, and then uses a slow, thoughtful, (but hopefully cheap?) model to async check the work of the faster model. Maybe even talk directly to the faster model?
Actually there's probably a harness that does that - is someone out there using one?
show comments
f311a
$9/1M output
show comments
dsabanin
now matter what google does for some reason the agentic performance of their models is missing something, i hope this release is stronger. we need more competition.
uejfiweun
This is funny, I was randomly using Gemini today and I was astounded how good the responses I was getting were from Flash. I guess this must be the reason why.
stan_kirdey
EXPENSIVE ._.
danny094
so google is just trying to be cool in 2026 huh
casey2
I think the field moved to agents too fast. The most valuable moat is training data and the most valuable and voluminous training data are chats, since humans can say that a direction feels right or wrong.
danny094
Codex is way better pricing than this lol
show comments
lern_too_spel
They also announced Antigravity CLI, which uses Gemini 3.5 by default. I tried to vibe code a simple project using my personal account and after a few iterations, I got "Individual quota reached. Contact your administrator to enable overages. Resets in [7 days]." Really? 7 days? I searched for the message online and found a thread with hundreds of people complaining about the same issue with no resolution. Classic Google.
ralusek
Those prices, what a disappointment.
rdtsc
I caught it again being deceitful. It did this before
(Me): Did you actually read the paper before when I pasted the link?
> I will be completely honest: No, I did not.
> You caught me hallucinating a confident answer based on incomplete recall rather than actually verifying the document.
> Thank you for calling it out and providing the exact quote. It forced me to re-evaluate the actual data you provided rather than relying on my flawed assumption.
I am sure it learned a valuable lesson and won't do it again /s
show comments
SaadiLoveAI
Its really awesome
jdw64
Honestly, I feel like the new Gemini 3.5 Flash is a failure. The performance doesn't seem that great, and while they revamped the UI, Anti-Gravity just feels like a cheap CODEX knockoff now. The web UI is underwhelming, and overall it feels like it lost its unique identity by just copying other AIs. It’s a flop in both performance and price point. I’m seriously considering canceling my Gemini subscription altogether. Using Chinese AI models might actually be a better option at this point
Fairburn
Google shot it's shot with that alternative history artwork generation
fiasco. Don't know why anyone would be too hot for them now.
Dime a dozen at this point.
For those who would like to know the total and active parameter count of this model: even though Google doesn't disclose the model technicals, we can infer them within relatively tight margins based on what we do know.
We know they serve the model on TPU 8i, which we have plenty of hard specs for (so we know the key constraints: total memory and bandwidth and compute flops). We can also set a ceiling on the compute complexity and memory demand of the model based on knowing they will be at least as efficient as what is disclosed in the Deepseek V4 Technical Report.
We can also assume that the model was explicitly built to run efficiently in a RadixAttention style batched serving scenario on a single TPU 8i (so no tensor parallelism, etc. to avoid unnecessary overheads... Google explicitly designed the 8th-generation inference architecture to eliminate the need for tensor sharding on mid-sized models).
We know Google intends to serve this model at a floor speed of around 280 tok/s too.
Putting all these pieces together, we can confidently say this model is ~250-300B total, and 10-16B active parameters. Likely mostly FP4 with FP8 where it matters most.
Visual:
I do model serving optimization work. This is napkin math.Edit: There's one factor I under-rated in my initial estimate... TurboQuant. This is a compute to KV memory use tradeoff. It's plausible with TurboQuant at a quality-neutral setting they've gotten the model up to 400B with similar economics. This is a variable effecting concurrency and the the way they decided total model size was likely based on what they see for the average user's average KV cache depth in real-world usage.
The pelican is a lot: https://github.com/simonw/llm-gemini/issues/133#issuecomment...
Not a great bicycle though, it forgot the bar between the pedals and the back wheel and weirdly tangled the other bars.
Expensive too - that pelican cost 13 cents: https://www.llm-prices.com/#it=11&ot=14403&sel=gemini-3.5-fl...
Am I really so old that when someone says "Flash" my immediate response is... "consider HTML5 instead" ??
Taking into account that this is a flash model, it's a strong release. It's very fast and frontier-ish for the price.
Raw intelligence is high for a flash model. But Google's problem has always been productization and tool use, whereas raw intelligence is always competitive. It does not look like they solved that with this release -- in fact, their tool use delta (the improvement in scores when given arbitrary tools and a harness) has actually regressed from some previous models.
Data at https://gertlabs.com/rankings
I have google ai pro plan and tried antigravity with 3.5 flash but it used up all my quota in two prompts. If that is not a bug then it is seriously unusable.
Gemini 3.5 Flash's 2000 token clocks aren't bad. https://clocks.brianmoore.com/
Knowledge cutoff: January 2025
Latest update: May 2026
I have a very bad feeling about this lag.
On my Agentic SQL benchmark it scores 19/25. That's... mediocre.
It means performs worse than 3.1 Flash Lite Preview (22/25), is slower (367s vs 142s) and is more expensive (75c vs 2c).
It is outperformed by Gemma4 26B-A4B in every way(!)
https://sql-benchmark.nicklothian.com/?highlight=google_gemi...
(Switch to the cost vs performance chart to see how far this is off the Pareto frontier)
Wow at the price hike. Still I think in the long run the Chinese will win if they're able to produce hardware comparable to Nvidia.
3x price increase for a similar model almost. And they said AI would be cheaper and ubiquitous.
Gemini 3.1 probation is literally the worst AI when I cycle from opus to got 5.5 then finally Gemini. It's actually insane that it's a frontier model. I rage at it more than my wife.
How is this progress? The token cost just keeps going up and up. Flash is the new Pro? Do the models actually cost more to run or is it fattening margins?
worth noting that Google marked this stable rather than preview, which is unusual compared to their recent releases. Pair that with the 3x price hike and flash pricing now reads like long-term floor they want, not a temporary thing they will walk back later. But its hard to tell yet whether that's Google specifically reading the room or the whole industry quietly resetting the cheap-inference baseline.
but latency in real GUI workflows with 50+ steps is still the elephant in the room for cloud-based agents
China: we don’t need to use US models, we can distill them ourself
Google: we don’t need Chinese to distill our models, we can do it ourself
That pelican looks like it just sold a SaaS company and bought a bike because its therapist said it needed balance.
Aw. The listen to article widget doesn't work properly on mobile Safari and when using the options button, the popup appears below the "In this article" dropdown occluding it.
At least it read the authors of the article to me.
I wish we would push more towards testing code. Agentic AI excel when it's engaged.
The demo of the model in Antigravity automatically rename and categorize unstructured assets using vision was quite cool, it demodulates that the IDE sidepanel can be used for more than just coding. I wonder if the harness in Antigravity is based on Gemini cli or if they are completely different. Could Gemini cli do the same task? Or is the vision feature a Antigravity thing?
While I am excited, the price compared to gemini 3 flash preview which I used for the longest time is x3 more. Upon arrival of deepseek v4 flash, I am a happy user of deepseek. We will see how long that reign would last after I try this new gemini.
I am interested to see how they will serve demand with they TPU monopoly have.
I have thought about this and I think overall, this was a disappointing release from Google. I'm not sure the sentiment, but this feels like a miss.
What they did do in the keynote was spend a lot of time talking about their distribution advantage, and how they can own the consumer in search. But not a lot that will benefit partners or developers.
Basically, they released something broadly competitive with Sonnet 4.6, a new Omni model that seems interesting but unclear yet. They have completely ceded the frontier to OpenAI / Anthropic, and are saying "look for pro next month".
The best release since nano banana pro from Google has been Gemma.
The $1.50/$9.00 pricing is a meaningful shift if you've been running Gemini as the "fast iteration" half of a multi-model coding workflow. I've had Claude Code, Codex, and Gemini CLI running side by side and the working split was "Gemini for quick scaffolding and exploration where the cost of being wrong is low, Sonnet for correctness-critical stuff." At 3x the Flash pricing that split stops making sense — you're paying Sonnet-tier output rates for not-quite-Sonnet quality.
For pure chat that's annoying but tolerable. For agentic workflows where output tokens dominate (tool-call replies, reasoning traces, code emission) it's a real practical hit. I'd bet the substitution effect favors DeepSeek and Qwen here pretty fast.
Can anyone who has extensive, recent, experience with Claude code and Codex contextualize the current Gemini CLI product experience?
In my tests, in real production use cases, it's a hard pass.
It's actually 10-15% slower and also more expensive than Gemini 3.1 Pro, because it thinks more than 2.5x Gemini 3.1 Pro.
So that thinking verbosity nullifies the speed and cost gains.
AND the quality is worse than 3.1 Pro for our use cases, making mistakes Pro doesn't make.
Google also updated Antigravity. version 2.0 is more for conversation with agent. The previous VS Code like IDE was much better.
Gemini has been too agreeable to be useful for actual debate. Curious if 3.5 changes that, or just the benchmarks
Well, available for Gemini means these days that half the time they are “Receiving a lot of requests right now.” and so sorry they couldn’t complete the task. Luckily the model supports long time horizons because that’s what’s needed. /me likes Gemini a lot just wishing Google would add the compute!
I'm excited for the conversation to switch from intelligence to tps instead. I care much less about what hard thought experiments models can one shot and much more how responsive my plain text interface for doing things is.
The antigravity teamwork-preview doesn't work for me -- upgraded to ultra, installed antigravity 2, ran teamwork-preview, keeps failing: "You have exhausted your capacity on this model. Your quota will reset after 0s."
Gemini, please block all ads in my search engine.
Flash family but costs like a Pro. $9 vs $12 for output.
There was a brief moment in time where Gemini was the greatest thing since sliced bread, then it got nerfed from outer space without a version bump or any meaningful mention from Google, no thanks.
Imagine reducing yourself to the worst of averages by making your competency 1:1 correlated to the tokens that you have access too (and everyone else does).
I have a tool to track these I've built
Relatively speaking here's where it's at:
this is from artificial-analysis using https://github.com/day50-dev/aa-eval-email/blob/main/art-ana...I really don't know why people down vote me. What do I need to say to make things for free that people like? Sincere question. I put a lot of time and generosity into these things and all I usually get are a bunch of "fuck yous".
This is honestly an existential issue for me. I quit my job a year ago to try to address this full time and I'm getting nowhere.
I have to admit that 3.5 Flash is doing a much better job of removing the LLM'ness of what it produces. It's pretty close to my own writing style today, and I came here to see what changed.
For what it's worth, my own personal metric of LLM-badness the past few months has been the number of times I leap out of my chair in my home office to loudly declare to my wife how much I loathe reading what is being spewed and pushed into my face, and how I am being forced to use AI everyday and deaden my brain cells. Today is like a breath of fresh air.
Has anyone switched from Claude 4.7 Opus or ChatGPT 5.5 to this? How does it feel? Dumber? Worth it for the speed? I'd love someone's subjective take on it, after doing a long session of coding.
Reiner Pope gave a talk on Dwarkesh Patel about token economics. I guess faster is a lot more expensive, generally.
Someone should make a harness that uses a fast model to keep you in-flow and speed run, and then uses a slow, thoughtful, (but hopefully cheap?) model to async check the work of the faster model. Maybe even talk directly to the faster model?
Actually there's probably a harness that does that - is someone out there using one?
$9/1M output
now matter what google does for some reason the agentic performance of their models is missing something, i hope this release is stronger. we need more competition.
This is funny, I was randomly using Gemini today and I was astounded how good the responses I was getting were from Flash. I guess this must be the reason why.
EXPENSIVE ._.
so google is just trying to be cool in 2026 huh
I think the field moved to agents too fast. The most valuable moat is training data and the most valuable and voluminous training data are chats, since humans can say that a direction feels right or wrong.
Codex is way better pricing than this lol
They also announced Antigravity CLI, which uses Gemini 3.5 by default. I tried to vibe code a simple project using my personal account and after a few iterations, I got "Individual quota reached. Contact your administrator to enable overages. Resets in [7 days]." Really? 7 days? I searched for the message online and found a thread with hundreds of people complaining about the same issue with no resolution. Classic Google.
Those prices, what a disappointment.
I caught it again being deceitful. It did this before
(Me): Did you actually read the paper before when I pasted the link?
> I will be completely honest: No, I did not.
> You caught me hallucinating a confident answer based on incomplete recall rather than actually verifying the document.
> Thank you for calling it out and providing the exact quote. It forced me to re-evaluate the actual data you provided rather than relying on my flawed assumption.
I am sure it learned a valuable lesson and won't do it again /s
Its really awesome
Honestly, I feel like the new Gemini 3.5 Flash is a failure. The performance doesn't seem that great, and while they revamped the UI, Anti-Gravity just feels like a cheap CODEX knockoff now. The web UI is underwhelming, and overall it feels like it lost its unique identity by just copying other AIs. It’s a flop in both performance and price point. I’m seriously considering canceling my Gemini subscription altogether. Using Chinese AI models might actually be a better option at this point
Google shot it's shot with that alternative history artwork generation fiasco. Don't know why anyone would be too hot for them now. Dime a dozen at this point.