GPT-6.1 Sol vs Gemini 4 Argon
Choose two or three models. Copy the URL to share your selection.
| Comparison | GPT-6.1 Solgpt-6.1-sol | Gemini 4 Argongemini-4-argon |
|---|---|---|
| Type | Chat | Chat |
| Best for | Near-flagship agentic coding and computer use at a lower price | Long-horizon coding, agents and million-token documents |
| TokenRex price | $2.00 in / $10.00 out per 1M tokens | $2.00 in / $10.00 out per 1M tokens |
| Cached input / 1M tokens | $0.10 per 1M tokens | $0.10 per 1M tokens |
| Cache write / 1M tokens | $2.50 per 1M tokens | No extra fee |
| Cached output | Not offered · standard output rate applies | Not offered · standard output rate applies |
| Web search | $10.00 per 1K searches | $14.00 per 1K searches |
| Market price | $2.00 in / $10.00 out per 1M tokens | $2.00 in / $10.00 out per 1M tokens |
| Context window (provider) | 1,050,000 tokens | 1,048,576 tokens |
| Input token limit (provider) | Within the context window | Within the context window |
| Maximum output | 128,000 tokens | 65,536 tokens |
| Knowledge cutoff | April 2026 | March 2026 |
| Vendor input modalities | Text, Image | Text, Image, Audio, Video |
| Vendor output modalities | Text | Text |
| TokenRex endpoints | POST /v1/chat/completions | POST /v1/chat/completions |
| Benchmarks | ||
| Benchmark evidence | 5 source-linked results | 19 source-linked results |
| DeepSWE v1.1 | 75.2% Self-reported by OpenAI in the GPT-6.1 Sol launch post (best of five reasoning efforts), September 2026. OpenAI · Introducing GPT-6.1 Sol | 77.9% Self-reported by Google in the Gemini 4 Argon model card, October 2026. Google DeepMind · Gemini 4 Argon model card |
| Terminal-Bench Science 0.1 | 57% Self-reported by OpenAI in the GPT-6.1 Sol launch post (max reasoning effort), September 2026. OpenAI · Introducing GPT-6.1 Sol | 57.6% Self-reported by Google in the Gemini 4 Argon model card, October 2026. Google DeepMind · Gemini 4 Argon model card |
| OSWorld 2.0 | 71.4% Self-reported by OpenAI in the GPT-6.1 Sol launch post (offline set, partial credit, best of five efforts), September 2026. OpenAI · Introducing GPT-6.1 Sol | — |
| AutomationBench 1.0.6 | 36.1% Self-reported by OpenAI in the GPT-6.1 Sol launch post (best of five efforts), September 2026. OpenAI · Introducing GPT-6.1 Sol | — |
| GDP.pdf | 32% Self-reported by OpenAI in the GPT-6.1 Sol launch post (best of five efforts), September 2026. OpenAI · Introducing GPT-6.1 Sol | — |
| Vals Index | — | 68.9% Self-reported by Google in the Gemini 4 Argon model card, October 2026. Google DeepMind · Gemini 4 Argon model card |
| AutomationBench | — | 51.3% Self-reported by Google in the Gemini 4 Argon model card (Score), October 2026. Google DeepMind · Gemini 4 Argon model card |
| Vals Finance Agent v2 | — | 65.4% Self-reported by Google in the Gemini 4 Argon model card, October 2026. Google DeepMind · Gemini 4 Argon model card |
| Harvey's Legal Agent Benchmark | — | 19.6% Self-reported by Google in the Gemini 4 Argon model card, October 2026. Google DeepMind · Gemini 4 Argon model card |
| FrontierSWE v2 | — | 55% Self-reported by Google in the Gemini 4 Argon model card, October 2026. Google DeepMind · Gemini 4 Argon model card |
| Vibe Code Bench | — | 91.9% Self-reported by Google in the Gemini 4 Argon model card, October 2026. Google DeepMind · Gemini 4 Argon model card |
| Terminal-bench 4.0 | — | 57.4% Self-reported by Google in the Gemini 4 Argon model card, October 2026. Google DeepMind · Gemini 4 Argon model card |
| PostTrainBench | — | 45.3% Self-reported by Google in the Gemini 4 Argon model card, October 2026. Google DeepMind · Gemini 4 Argon model card |
| LABBench 2 | — | 88.8% Self-reported by Google in the Gemini 4 Argon model card, October 2026. Google DeepMind · Gemini 4 Argon model card |
| RiemannBench | — | 76% Self-reported by Google in the Gemini 4 Argon model card, October 2026. Google DeepMind · Gemini 4 Argon model card |
| GraphWalks BFS (up to 128K) | — | 99.7% Self-reported by Google in the Gemini 4 Argon model card (F1), October 2026. Google DeepMind · Gemini 4 Argon model card |
| GraphWalks BFS (256K to 1M) | — | 84.2% Self-reported by Google in the Gemini 4 Argon model card (F1), October 2026. Google DeepMind · Gemini 4 Argon model card |
| Agent's Last Exam | — | 39.5% Self-reported by Google in the Gemini 4 Argon model card (Pass rate), October 2026. Google DeepMind · Gemini 4 Argon model card |
| OSWorld-2.0 (offline subset) | — | 69.2% Self-reported by Google in the Gemini 4 Argon model card (Partial score), October 2026. Google DeepMind · Gemini 4 Argon model card |
| Chartography | — | 71.6% Self-reported by Google in the Gemini 4 Argon model card, October 2026. Google DeepMind · Gemini 4 Argon model card |
| LVBench | — | 91.7% Self-reported by Google in the Gemini 4 Argon model card, October 2026. Google DeepMind · Gemini 4 Argon model card |
| CWE-bench v1 | — | 68% Self-reported by Google in the Gemini 4 Argon model card, October 2026. Google DeepMind · Gemini 4 Argon model card |
No overall score, winner or cost-versus-score frontier is calculated without comparable, attributable benchmark evidence. Different test configurations appear separately. Vendor capabilities are distinct from TokenRex API support.
— means no published value or no matching capability. Provider token limits are not tested gateway guarantees; TokenRex media controls and response formats are listed separately.
GPT-6.1 Sol
Sources and verification
Provider specifications describe the upstream model, not a guarantee of every feature through TokenRex. Prices come from the enabled catalog; benchmark results belong to the exact tested model.
- OpenAI API · GPT-6.1 Sol model
Vendor-reported
Last checked - OpenAI · Introducing GPT-6.1 Sol
Vendor-reported
Last checked - OpenAI · GPT-6.1 Sol system card addendum
Vendor-reported
Last checked
Research notes (2)
- Published provider limits; maximum-capacity requests have not been independently exercised through TokenRex.
- All benchmark scores are self-reported by OpenAI at launch (29 September 2026); TokenRex has not re-run them.
Gemini 4 Argon
Sources and verification
Provider specifications describe the upstream model, not a guarantee of every feature through TokenRex. Prices come from the enabled catalog; benchmark results belong to the exact tested model.
- Gemini API · Gemini 4 Argon model specifications
Vendor-reported
Last checked - Google DeepMind · Gemini 4 Argon model card
Vendor-reported
Last checked - Google Blog · Introducing Gemini 4 Argon
Vendor-reported
Last checked
Research notes (2)
- Published provider limits; maximum-capacity requests have not been independently exercised through TokenRex. Standard requests allow up to 65,536 output tokens. Google's long-decode mode (output up to 1,048,576 tokens minus input) is enabled with background=true — the TokenRex chat endpoint accepts this parameter (verified live on 2026-10-14), but a full 1M-token output has not been exercised, so the default 65,536-token output limit is shown.
- All benchmark scores are self-reported by Google in the official model card; TokenRex has not re-run them.
Popular comparisons
- GPT-6 Sol vs Claude Opus 5.5
- GPT-6 Sol vs Gemini 4 Argon
- Claude Opus 5.5 vs Gemini 4 Argon
- GPT-6.1 Sol vs GPT-6 Sol
- GPT-6 Astra vs Claude Sonnet 5
- GPT-6 Astra vs Gemini 3.1 Pro
- Claude Sonnet 5 vs Gemini 3.1 Pro
- Claude Opus 5.5 vs Claude Sonnet 5
- GPT-5.5 vs Claude Sonnet 5
- GPT-5.5 vs Gemini 2.5 Pro
- GPT-5 vs Gemini 2.5 Pro
- GPT-6 Luna vs Gemini 3.8 Flash
- Claude Haiku 4.5 vs Gemini 3.8 Flash
- GPT-5 Mini vs Gemini 2.5 Flash
- GPT-5 Nano vs Gemini 2.5 Flash Lite
- GPT-5.4 Mini vs Claude Haiku 4.5
- GPT-6 Sol vs Claude Sonnet 5
- GPT-6 Sol vs GPT-6 Astra
- GPT-6 Sol vs Claude Fable 5.1
- GPT-6.1 Sol vs Claude Opus 5.5
- GPT-6.1 Sol vs Gemini 4 Argon
- Claude Opus 5.5 vs Claude Opus 5
- Claude Fable 5.1 vs Claude Opus 5.5
- Claude Fable 5.1 vs Gemini 4 Argon
- Gemini 4 Argon vs Gemini 3.1 Pro
- GPT-6 Astra vs GPT-6 Luna
- GPT-6 Luna vs Claude Haiku 4.5
- GPT-5.6 Sol vs GPT-6 Sol
- GPT-5.6 Sol vs Claude Opus 5.5
- GPT-5.6 Terra vs Claude Sonnet 5
- GPT-5.6 Luna vs Gemini 3.8 Flash
- GPT-5.5 Pro vs Claude Opus 5.5
- GPT-5.5 vs GPT-5.4
- GPT-5.4 vs Gemini 3.1 Pro
- GPT-5.4 Nano vs Gemini 3.1 Flash Lite
- GPT-5.2 vs GPT-5
- Gemini 3.8 Flash vs Gemini 3.5 Flash
- Gemini 2.5 Pro vs Gemini 3.1 Pro
- Gemini 2.5 Flash vs Gemini 3 Flash
- GPT Image 2 vs Gemini 3 Pro Image
- GPT Image 2.5 Sunburst vs GPT Image 2
- Gemini 3.1 Flash Image vs GPT Image 1 Mini
- Gemini 3 Pro Image vs Gemini 3.1 Flash Image
- Veo 3.1 vs Gemini Omni 1.1 Flash
- Veo 3.1 vs Veo 3.1 Fast
- GPT-4o Mini TTS vs Gemini 2.5 Flash TTS
- GPT-4o Transcribe vs Gemini 3.5 Transcribe
- GPT-4o Transcribe vs GPT-4o Mini Transcribe
- Text Embedding 3 Large vs Gemini Embedding 2
- Text Embedding 3 Small vs Gemini Embedding 001