GPT-6.1 Sol vs Gemini 4 Argon vs Claude Sonnet 5.5
Too close to call on our weighted score (Gemini 4 Argon 74, GPT-6.1 Sol 72, Claude Sonnet 5.5 72). The right pick depends on what you value most.
OpenAI
GPT-6.1 Sol
72/100- ECI167.8
- Price$2.00 / $10.00
- Context1.05M
Google
Gemini 4 Argon
74/100- ECI166.1
- Price$2.00 / $10.00
- Context1.05M
Anthropic
Claude Sonnet 5.5
72/100- ECI166.7
- Price$2.00 / $10.00
- Context1M
Too close to call
It is close. Our weighted score puts them within 2 points (Gemini 4 Argon 74/100, GPT-6.1 Sol 72/100, Claude Sonnet 5.5 72/100), so choose by what matters most for your work: GPT-6.1 Sol for raw capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityGPT-6.1 SolCapabilities Index (ECI): GPT-6.1 Sol 167.8 · Claude Sonnet 5.5 166.7 · Gemini 4 Argon 166.1
- Lowest priceSame priceGPT-6.1 Sol $4.00 · Gemini 4 Argon $4.00 · Claude Sonnet 5.5 $4.00 per 1M tokens (3:1 blend)
- Longest contextGPT-6.1 Sol and Gemini 4 ArgonGPT-6.1 Sol 1,050,000 · Gemini 4 Argon 1,048,576 · Claude Sonnet 5.5 1,000,000 tokens
- Widest inputsGemini 4 ArgonGPT-6.1 Sol: Text, Images, PDFs · Gemini 4 Argon: Text, Images, PDFs, Audio, Video · Claude Sonnet 5.5: Text, Images, PDFs
- Self-hostingNo open weightsAll three are available only through APIs
| Measure | Weight | GPT-6.1 Sol | Gemini 4 Argon | Claude Sonnet 5.5 |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 99 | 96 | 97 |
| Price | 25% | 20 | 20 | 20 |
| Inputs & features | 15% | 80 | 100 | 80 |
| Context window | 10% | 61 | 61 | 60 |
| Overall | 100% | 72/100 | 74/100 | 72/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 167.8 (best) | 166.1 | 166.7 |
| ECI rank | #4 of 165 (best) | #7 of 165 | #5 of 165 |
| GPQA DiamondGraduate-level science questions | 95.4% | 96.4% (best) | 95.6% |
| FrontierMath Tiers 1–3Research-level mathematics | 93.7% (best) | 86.0% | 88.8% |
| OTIS Mock AIME 2024–2025Competition mathematics | 100% | 100% | 100% |
| SimpleQA VerifiedShort factual questions | 73.9% | 76.0% (best) | 46.5% |
| Price per million tokens | |||
| Input | $2.00 | $2.00 | $2.00 |
| Output | $10.00 | $10.00 | $10.00 |
| Cached input | $0.10 | $0.10 | $0.10 |
| Blended (3:1) | $4.00 | $4.00 | $4.00 |
| Long-context rate | Over 272K: $4.00 / $15.00 | Same rate | Same rate |
| Price source | Official OpenAI API | Official Google API | Official Anthropic API |
| Limits | |||
| Context window | 1,050,000 tokens (best) | 1,048,576 tokens | 1,000,000 tokens |
| Max output | 128,000 tokens (best) | 65,536 tokens | 128,000 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | Yes | Yes | Yes |
| Audio | No | Yes | No |
| Video | No | Yes | No |
| Reasoning | Yeslow · medium · high · xhigh · max | Yeslow · medium · high | Yeslow · medium · high · xhigh · max |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | Yes |
| Availability | |||
| Weights | Proprietary | Proprietary | Proprietary |
| API model ID | gpt-6.1-sol | gemini-4-argon | claude-sonnet-5-5 |
| API providers | 33 | 24 | 34 (best) |
| Released | Sep 29, 2026 | Oct 13, 2026 | Sep 28, 2026 |
| Knowledge cutoff | Apr 30, 2026 | Mar 2026 | Jun 2026 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
GPT-6.1 Sol$40.00
Gemini 4 Argon$40.00
Claude Sonnet 5.5$40.00
Which should you choose?
Which is better: GPT-6.1 Sol, Gemini 4 Argon or Claude Sonnet 5.5?
It is close. Our weighted score puts them within 2 points (Gemini 4 Argon 74/100, GPT-6.1 Sol 72/100, Claude Sonnet 5.5 72/100), so choose by what matters most for your work: GPT-6.1 Sol for raw capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, GPT-6.1 Sol, Gemini 4 Argon or Claude Sonnet 5.5?
GPT-6.1 Sol, Gemini 4 Argon and Claude Sonnet 5.5 cost the same: $2.00 input / $10.00 output per million tokens.
Which scores higher on benchmarks?
GPT-6.1 Sol scores higher on the Capabilities Index (ECI): GPT-6.1 Sol 167.8 (#4 of 165), Claude Sonnet 5.5 166.7 (#5 of 165) and Gemini 4 Argon 166.1 (#7 of 165). The confidence ranges of the top two overlap (164.3–172.5 vs 163.6–171.3), so treat the gap as small. On individual benchmarks: GPQA Diamond — Gemini 4 Argon 96.4%, Claude Sonnet 5.5 95.6%, GPT-6.1 Sol 95.4%; FrontierMath Tiers 1–3 — GPT-6.1 Sol 93.7%, Claude Sonnet 5.5 88.8%, Gemini 4 Argon 86.0%; OTIS Mock AIME 2024–2025 — GPT-6.1 Sol 100%, Gemini 4 Argon 100%, Claude Sonnet 5.5 100%; SimpleQA Verified — Gemini 4 Argon 76.0%, GPT-6.1 Sol 73.9%, Claude Sonnet 5.5 46.5%.
Which is better for coding?
There are no published SWE-bench Verified results for GPT-6.1 Sol, Gemini 4 Argon and Claude Sonnet 5.5 yet, so there is no like-for-like coding score. On overall capability, GPT-6.1 Sol leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.
Which has the bigger context window?
GPT-6.1 Sol and Gemini 4 Argon have the largest context windows (1,050,000 and 1,048,576 tokens), against 1,000,000 for Claude Sonnet 5.5. Maximum output per response: GPT-6.1 Sol up to 128,000, Gemini 4 Argon up to 65,536, Claude Sonnet 5.5 up to 128,000 tokens.
Which can read images, PDFs, audio or video?
GPT-6.1 Sol accepts text, images and PDFs; Gemini 4 Argon accepts text, images, PDFs, audio and video; Claude Sonnet 5.5 accepts text, images and PDFs. Gemini 4 Argon handles the widest range of inputs.
Are any of these open source?
No. GPT-6.1 Sol, Gemini 4 Argon and Claude Sonnet 5.5 are proprietary and only available through APIs and apps.
Which is newer?
Gemini 4 Argon is the newest, released Oct 13, 2026. GPT-6.1 Sol came out Sep 29, 2026; Claude Sonnet 5.5 came out Sep 28, 2026. Knowledge cutoff: GPT-6.1 Sol Apr 30, 2026, Gemini 4 Argon Mar 2026, Claude Sonnet 5.5 Jun 2026.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Nov 2, 2026.