Google Gemini vs other AI models performance (2026): benchmarks, pricing and our verdict
How Gemini 4 Argon and Carbon stack up against Claude Opus 5.5, GPT-6, Grok 4.7, Muse Wonder and DeepSeek on leaderboards, API prices and speed.
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Google's best model doesn't win every chart. In this Google Gemini vs other AI models performance check, Gemini 4 Argon leads the LMArena text ranking and hallucinates far less than its rivals, but Claude Opus 5.5 and GPT-6 Astra score higher on the Artificial Analysis Intelligence Index and lead the coding boards. Google's newer Gemini 4 Carbon tops that index at 59, yet almost nobody can use it yet. I think Argon is a top-three model with a price edge that ends on November 30.
The AI Future didn't run its own tests for this piece. It compares two independent leaderboards (Artificial Analysis and LMArena), published benchmarks, official API price lists and measured speeds, all checked on November 2, 2026. Scores published by a model's own maker are labelled vendor-reported. If you want the consumer apps (plans, free tiers, features), our same-day AI assistant comparison of Google vs other AI covers them.
Quick verdict: who wins for which use case
- Top score overall goes to Gemini 4 Carbon at 59 on the Artificial Analysis leaderboard, one point ahead of Claude Opus 5.5 at its max setting. Carbon is limited to "a subset of cyber defenders" for now, Google's announcement says.
- Among models you can buy today, Claude Opus 5.5 (58) and GPT-6 Astra (57) lead. Gemini 4 Argon scores 50 at its high setting.
- For chat answers that people prefer in blind votes, Argon ranks first on LMArena's text board at 1524 (preliminary).
- For web apps and coding, Claude Opus 5.5 leads LMArena's WebDev board at 1807; Argon is ninth.
- For value, GPT-6.1 Sol scores 55 at about $1.27 per index task, a fraction of what Opus 5.5 or Argon cost to run.
- For raw output speed among frontier models, Meta's Muse Wonder is the quickest at 192 tokens a second.
Our take: Argon is probably the best Google model you can call today, and it's the most careful about facts. It isn't the strongest model on the market, though. Honestly, if I were picking one API for mixed work this month, I'd start with GPT-6.1 Sol for cost and keep Opus 5.5 for hard coding jobs.
Side-by-side comparison table
| Model (maker) | AA Intelligence Index | LMArena text | API price, input / output per 1M tokens | Context window | Output speed (tokens/s) |
|---|---|---|---|---|---|
| Gemini 4 Carbon (Google) | 59 | Not listed | $2 / $10 at launch (announced) | 1M | 95 |
| Gemini 4 Argon (Google) | 50 (high) | 1524, 1st (preliminary) | $2 / $10 to Nov 30, then $4 / $20 | 1M, shared by input and output | 83 |
| Claude Opus 5.5 (Anthropic) | 58 (max) | 1508, 3rd | $4 / $20 | 1M | 96 |
| Claude Fable 5.1 (Anthropic) | 50 (xhigh) | 1502, 6th | $10 / $50 | 1M | 63 |
| GPT-6 Astra (OpenAI) | 57 (max) | Outside top 25 | $10 / $50 | 1.05M | 74 |
| GPT-6.1 Sol (OpenAI) | 55 (max) | 1484, 22nd | $2 / $10 | 1M | 91 |
| Grok 4.7 (SpaceXSI, formerly xAI) | 35 (high) | Outside top 25 | $2 / $6 | 500K | 76 |
| Muse Wonder (Meta) | 43 (max) | 1509, 2nd | $4 / $20 | 1.05M | 192 |
| DeepSeek V4.1 Flash (DeepSeek) | 32 (max) | Outside top 25 | $0.30 / $1.20 peak, half off-peak | 1M | 170 |
Sources: Artificial Analysis (index, speed and context, checked November 2, 2026), Developers Digest reporting the LMArena leaderboard as of October 17, Gemini API pricing, OpenAI API pricing, Artificial Analysis for Opus 5.5's price, Apidog for Fable 5.1 and Astra limits, SpaceXSI, TechCrunch and DeepSeek.
One caveat on the index column. Artificial Analysis scores each reasoning setting separately, and Argon's only listed entry is "high", while rivals appear at "max". That likely flatters the competition a little.
Features compared
Context windows and output limits
Most frontier models now take about a million tokens. Argon's 1,048,576 tokens are shared by input, thinking and output, and a plain request stops at 65,536 output tokens; longer answers need background mode, Apidog found. Google calls this "an industry-leading 1M unified input-output token limit" in its Argon launch post.
GPT-6 Astra takes 1,050,000 tokens but caps input at 922K, and prompts over 272K tokens cost twice as much for input. Opus 5.5 offers 1M with a 128K output cap. Grok 4.7 is the outlier at 500,000 tokens, per the model list. DeepSeek allows up to 384K tokens of output, which is generous.
(Meta's older Llama 4 Scout still lists a 10M-token window on Artificial Analysis, for what it's worth, though it has no current index score.)
Token use and reasoning settings
List prices only tell half the story. Running the full index, Argon generated 110M tokens against a median of 70M, according to its Artificial Analysis profile. Opus 5.5 at max used 220M, which AA calls "very verbose". GPT-6 Astra at max used just 54M, and Grok 4.7 at xhigh used 140M.
That's why a cheap per-token model can still be expensive per job.
Speed and latency
Argon produces about 83 tokens a second, and AA rates it "slower than average and somewhat verbose." Its time to first token is 40.49 seconds at the high setting, against a 6.15-second median for its price tier. Reasoning models think before they answer, so that wait includes thinking time. Opus 5.5 at max takes far longer to start (721 seconds on AA's runs), then outputs at 96 tokens a second.
Meta's Muse Wonder and DeepSeek V4.1 Flash are the quick ones, at 192 and 170 tokens a second. I'd guess most chat users won't notice the gap, but agents that loop hundreds of times will.
Availability
Argon became generally available on October 13 through the paid Gemini API, with no free API tier. Carbon is restricted. Meta's stronger Muse Wonder Full can't be reached through the API at all: it's only in Muse Code plans from $50 a month, The Batch reports, and plain Wonder is still labelled preview, eesel notes. DeepSeek V4.1 Flash is the highest-ranked open-weights model on Artificial Analysis, so you can run it yourself.
Quality of output: benchmarks side by side
We didn't run prompts through these models. For a published three-prompt test of Argon against GPT-6 Sol, see our Gemini AI vs ChatGPT comparison. Below are the independent results first, then the vendor-reported ones.
Independent results
Artificial Analysis recently moved its index to version 5.0, Google's Carbon post says. Argon scored 53 at launch on the earlier version, level with GPT-6 Astra, The Next Web reported; it's 50 now.
Facts are Argon's strongest area. It hallucinated on 15% of AA-Omniscience questions, against 51% for GPT-6 Astra and 54% for GPT-6.1 Sol. It also answered fewer correctly: 50%, against 63% for Astra. So it says "I don't know" more often, which I think is the right trade for research and legal work.
Coding is weaker. On Terminal Bench 4, Argon scored 57%, behind Claude Sonnet 5.5 (64%), Opus 5.5 (60%) and Astra (59%). It did rank first on AutomationBench-AA, a business-software test, at 78%.
On LMArena, where people vote between two anonymous answers, Argon led the text board with 1524 points from 4,904 votes as of October 17, Developers Digest shows. Muse Wonder (1509) and Opus 5.5 (1508) followed. The WebDev board looks very different: Opus 5.5 first at 1807, GPT-6 Astra second at 1777, Argon ninth. Cursor reported 52.8% for Argon on its CursorBench at default effort, "on par with Opus 5.5," as Apidog quotes.
Vendor-reported results
Google's launch table puts Argon ahead on 13 of 19 rows. These are Google's figures, and Google sources rival scores mostly from the other vendors' own reports, so harnesses and effort settings differ.
| Benchmark (vendor-reported) | Gemini 4 Argon | GPT-6 Astra | Claude Opus 5.5 | Claude Fable 5.1 |
|---|---|---|---|---|
| Vals Index | 68.9% | 63.1% | 67.0% | 65.8% |
| DeepSWE v1.1 (coding) | 77.9% | 74.1% | 74.2% | 67.4% |
| GraphWalks 256K to 1M (long context) | 84.2% | 71.8% | 66.8% | 65.0% |
| FrontierSWE v2 (coding) | 55.0% | 65.5% | 62.3% | 56.3% |
| Terminal-bench 4.0 | 57.4% | 58.2% | 66.4% | 57.9% |
Source: Google's table as compiled by Apidog, October 15, 2026. Opus 5.5's Terminal-bench figure is Anthropic's own, at xhigh effort.
Carbon's numbers are vendor-reported too: 88.2% on SEC-bench Pro, 54.8% on ExploitGym and 71.0% on CWE-bench, plus fourth place (1768) on WebDev Arena, Google says. Meta's own 14-row table shows Muse Wonder Full tying Opus 5.5 at six wins each, by eesel's count; plain Wonder wins one. Meta also claims Wonder beats Fable, Opus and Astra on its MemoryBench memory test, TechCrunch reported.
Pricing compared
Prices are standard API rates in US dollars per million tokens, checked November 2, 2026. The last column is what Artificial Analysis paid, on average, per task in its index, which captures how many tokens each model burns.
| Model | Input | Output | Cost per AA index task |
|---|---|---|---|
| Gemini 4 Argon | $2, then $4 from Dec 1 | $10, then $20 from Dec 1 | $7.68 (at $4 / $20) |
| Gemini 4 Carbon | $2 at launch | $10 at launch | $7.76 |
| Claude Opus 5.5 | $4 | $20 | $10.04 (max) |
| Claude Fable 5.1 | $10 | $50 | $10.85 (xhigh) |
| GPT-6 Astra | $10 | $50 | $6.24 (max) |
| GPT-6.1 Sol | $2 | $10 | $1.27 (max) |
| Grok 4.7 | $2 | $6 | $6.18 (high) |
| Muse Wonder | $4 | $20 | $6.95 (max) |
| DeepSeek V4.1 Flash | $0.30 peak, $0.15 off-peak | $1.20 peak, $0.60 off-peak | $0.60 (max) |
Sources: Gemini API pricing, Google, Anthropic and Artificial Analysis, Apidog, OpenAI, SpaceXSI, TechCrunch, DeepSeek and the Artificial Analysis leaderboard.
Argon's half-price offer runs through November 30. From December 1 it costs exactly what Opus 5.5 costs, and Opus scores eight points higher on the index. Batch and Flex requests halve Argon's rates, which helps for overnight jobs.
Grok 4.7 surprised me. Its token prices are among the lowest here, but it used so many tokens that each index task cost $6.18, close to GPT-6 Astra. GPT-6.1 Sol is the clear value pick among closed models. DeepSeek is cheaper still, with off-peak rates at half the peak price (peak runs 01:00 to 04:00 and 06:00 to 10:00 UTC on weekdays), but it scores 32.
Reviewer and user reactions
Gemini 4 Argon
Promptslove built five apps with Argon and scored the set 17 out of 25, summing it up as "Strong at 3D, weak at layout" in its review. That echoes Bloomberg's sources inside Google, who described Argon's coding as uneven, per The Next Web. Google called that characterisation inaccurate.
Claude Opus 5.5
Tom's Guide's Amanda Caswell picked Claude in four of five everyday tests against ChatGPT-6. "Claude Opus 5.5 is the one I'd reach for when the task requires judgment," she wrote. She also warned that it's easier to hit Claude's usage limits.
OpenAI's GPT-6 models
In the same piece, Caswell liked ChatGPT-6's short answers: "The brevity of ChatGPT-6 means less fluff, which in my eyes is always a plus." That fits AA's token counts, where Astra at max is "fairly concise". Our ChatGPT GPT-6 review covers the model in the app.
Meta Muse Wonder
eesel's reviewer read Meta's docs and benchmark table rather than the press release. Their verdict: "Plain Wonder is a solid model at a price that gives you no reason to switch from Opus 5.5 yet."
Grok 4.7 and DeepSeek
Artificial Analysis places Grok 4.7 at xhigh "below average among comparable models" on its model page. Our Grok vs Gemini comparison covers the app side. DeepSeek V4.1 Flash, released September 10, leads the open-weights models on the index, though at 32 it sits well behind the closed frontier.
Which one should you choose?
- Pick Gemini 4 Argon for fact-heavy research, legal or finance work, and very long documents, especially while the $2 / $10 rate lasts.
- Pick Claude Opus 5.5 for coding agents and web front ends. Anthropic itself suggests starting with Opus 5.5 for most workloads, per its models overview.
- Pick GPT-6.1 Sol when cost per finished task matters more than the last few index points.
- Pick DeepSeek V4.1 Flash if you need open weights or very low prices, and can live with a lower score.
- Wait on Gemini 4 Carbon. It's priced like Argon and scores higher, but Google hasn't given a date for developers.
I'd expect the table to look different by Christmas. Argon's price doubles on December 1, and Google says Carbon will reach developers "as soon as possible". If you're new to the jargon, our explainer on what a token is in AI helps with the pricing maths, and our list of free AI models covers cheaper options.
FAQ
Is Gemini better than ChatGPT, Claude and Grok?
Not across the board. Gemini 4 Argon leads LMArena's text ranking and had the lowest hallucination rate of any high-scoring model in Artificial Analysis testing at launch. Claude Opus 5.5 and GPT-6 Astra score higher on the Intelligence Index and on coding boards. Grok 4.7 scores lower than all three.
What is Google's most powerful Gemini model right now?
Gemini 4 Carbon, announced October 28, scores 59 on the Artificial Analysis Intelligence Index, the highest of any model. It's limited to selected cyber defenders. Gemini 4 Argon is the most powerful Gemini model generally available.
How much does the Gemini 4 Argon API cost?
It's $2 per million input tokens and $10 per million output tokens until November 30, 2026, then $4 and $20.
Which AI model is the fastest?
Among frontier models, Meta's Muse Wonder outputs about 192 tokens a second on Artificial Analysis, and DeepSeek V4.1 Flash about 170. Argon manages around 83. Smaller models such as Celeris-1 go much faster, at 1,712 tokens a second, but score far lower.
Can you trust vendor-reported benchmarks?
Treat them with care. Google's own table notes that rival scores come mostly from the other companies' self-reported numbers, and test setups differ. Independent leaderboards such as Artificial Analysis and LMArena run every model the same way, so they're probably the fairer comparison.
