GPT-6.1 Sol is an upgrade to GPT-6 Sol from OpenAI, positioned below the flagship GPT-6 Astra in the GPT-6 series. It is suited for agentic coding, computer use, document-heavy professional work, and multi-step business workflow automation, and approaches Astra-level results on these tasks at a much lower cost. Compared with GPT-6 Sol, it makes fewer factual errors and is more reliable at respecting explicit restrictions and user intent during agentic tasks.
Providers
Different companies host the same model. OpenRouter routes your request to one of them based on the routing mode you pick: Balanced (price + speed), Nitro (fastest), or Floor (cheapest).
| $2.00 | $10.00 | $0.10 | 4.92s | 47 tok/s | ||
| $2.00 | $10.00 | $0.10 | 2.43s | 41 tok/s | ||
| $2.00 | $10.00 | $0.10 | 4.41s | 37 tok/s | ||
Not used in Standard routing:Why these endpoints are not used | ||||||
Flex | $1.00 | $5.00 | $0.05 | 7.10s | 42 tok/s | |
| $2.20 | $11.00 | $0.11 | 5.33s | 35 tok/s | ||
| $2.20 | $11.00 | $0.11 | 5.11s | 31 tok/s | ||
| $2.20 | $11.00 | $0.11 | 4.13s | 38 tok/s | ||
Fast | $4.00 | $20.00 | $0.20 | 2.56s | 60 tok/s | |
Ultrafast | $12.00 | $60.00 | $0.60 | 1.76s | 78 tok/s | |
- Input $2.00 / Output $10.0047 tok/s100.00% uptime
- Input $2.00 / Output $10.0041 tok/s100.00% uptime
- Input $2.00 / Output $10.0037 tok/s68.49% uptime
- Not used in Standard routing:Why these endpoints are not used
- Input $1.00 / Output $5.0042 tok/s100.00% uptimeFlex
- Input $2.20 / Output $11.0035 tok/s100.00% uptime
- Input $2.20 / Output $11.0031 tok/s100.00% uptime
- Input $2.20 / Output $11.0038 tok/s100.00% uptime
- Input $4.00 / Output $20.0060 tok/s100.00% uptimeFast
- Input $12.00 / Output $60.0078 tok/s100.00% uptimeUltrafast
Pricing
The average price customers actually pay for this model, next to the prices providers post. Caching and discounts mean the price actually paid is often well below the listed one.
Weighted average
GPT-6.1 Sol — Price history
| $0.354 | $10.07 | 90.2% | 2.3% | ||
| $0.371 | $10.10 | 89.8% | 67.1% | ||
| $0.657 | $10.06 | 80.7% | 16.3% | ||
Not used in Standard routing:Why these endpoints are not used | |||||
Flex | $0.127 | $5.03 | 93.8% | 10.6% | |
| $0.434 | $11.02 | 87.9% | 1.2% | ||
| $0.483 | $12.07 | 88.5% | 1.4% | ||
| $0.518 | $11.11 | 84.6% | 0.0% | ||
Fast | $1.011 | $20.50 | 84.6% | 1.0% | |
Ultrafast | $2.220 | $60.52 | 89.1% | 0.1% | |
- Effective in $0.354 / Effective out $10.07Token share2.3%
- Effective in $0.371 / Effective out $10.10Token share67.1%
- Effective in $0.657 / Effective out $10.06Token share16.3%
- Not used in Standard routing:Why these endpoints are not used
- Effective in $0.127 / Effective out $5.03FlexToken share10.6%
- Effective in $0.434 / Effective out $11.02Token share1.2%
- Effective in $0.483 / Effective out $12.07Token share1.4%
- Effective in $0.518 / Effective out $11.11Token share0.0%
- Effective in $1.011 / Effective out $20.50FastToken share1.0%
- Effective in $2.220 / Effective out $60.52UltrafastToken share0.1%
Performance
Throughput is how fast the model writes (tokens per second — higher is better). Latency is total round-trip time (lower is better). TTFT is time-to-first-token — how long before you see anything appear (lower is better).
P50, best across providers
P50, best provider
Uptime
Uptime is the percentage of the past 3 days that at least one provider was responding to requests. Availability is the percentage of time that inference was successfully served. OpenRouter continuously monitors and uses the next-best provider when one returns an error.
Availability over the last 3 days
Last 72 hoursAvailability over the last 24 hours
When an error occurs in an upstream provider, we can recover by routing to another healthy provider, if your request filters allow it. You can access per-provider uptime data programmatically through the Endpoints API. Learn more about our load balancing and provider routing options.
Benchmarks
Scores on standardized evaluations and this model’s own outputs on shared benchmark prompts. Higher percentages are better — and each rank shows where this model lands among the models evaluated on that source.
| Source | Benchmark | Score |
|---|---|---|
| Artificial Analysis | GPT-6.1 Sol (Max) Intelligence Index | 54.6 |
| Artificial Analysis | GPT-6.1 Sol (Max) HLE | 52.9% |
| Artificial Analysis | GPT-6.1 Sol (Max) AA-LCR | 83.0% |
| Artificial Analysis | GPT-6.1 Sol (Max) GDPval-AA | 55.4% |
| Artificial Analysis | GPT-6.1 Sol (Max) CritPt | 31.7% |
| Artificial Analysis | GPT-6.1 Sol (Max) SciCode | 54.2% |
| Artificial Analysis | GPT-6.1 Sol (Max) Terminal-Bench 4.0 | 56.1% |
| Artificial Analysis | GPT-6.1 Sol (Max) AA-Omniscience Accuracy | 61.8% |
| Artificial Analysis | GPT-6.1 Sol (Max) AA-Omniscience Non-Hallucination Rate | 48.1% |
| Artificial Analysis | GPT-6.1 Sol (Medium) Intelligence Index | 46.3 |
| Artificial Analysis | GPT-6.1 Sol (Medium) HLE | 49.9% |
| Artificial Analysis | GPT-6.1 Sol (Medium) AA-LCR | 83.3% |
| Artificial Analysis | GPT-6.1 Sol (Medium) GDPval-AA | 48.0% |
| Artificial Analysis | GPT-6.1 Sol (Medium) CritPt | 27.7% |
| Artificial Analysis | GPT-6.1 Sol (Medium) SciCode | 53.2% |
| Artificial Analysis | GPT-6.1 Sol (Medium) Terminal-Bench 4.0 | 48.0% |
| Artificial Analysis | GPT-6.1 Sol (Medium) AA-Omniscience Accuracy | 59.6% |
| Artificial Analysis | GPT-6.1 Sol (Medium) AA-Omniscience Non-Hallucination Rate | 51.9% |
| Artificial Analysis | GPT-6.1 Sol (Xhigh) Intelligence Index | 52.5 |
| Artificial Analysis | GPT-6.1 Sol (Xhigh) HLE | 52.6% |
| Artificial Analysis | GPT-6.1 Sol (Xhigh) AA-LCR | 79.7% |
| Artificial Analysis | GPT-6.1 Sol (Xhigh) GDPval-AA | 52.7% |
| Artificial Analysis | GPT-6.1 Sol (Xhigh) CritPt | 31.7% |
| Artificial Analysis | GPT-6.1 Sol (Xhigh) SciCode | 55.7% |
| Artificial Analysis | GPT-6.1 Sol (Xhigh) Terminal-Bench 4.0 | 54.0% |
| Artificial Analysis | GPT-6.1 Sol (Xhigh) AA-Omniscience Accuracy | 61.1% |
| Artificial Analysis | GPT-6.1 Sol (Xhigh) AA-Omniscience Non-Hallucination Rate | 52.0% |
| Artificial Analysis | GPT-6.1 Sol (High) Intelligence Index | 50.3 |
| Artificial Analysis | GPT-6.1 Sol (High) HLE | 51.4% |
| Artificial Analysis | GPT-6.1 Sol (High) AA-LCR | 82.3% |
| Artificial Analysis | GPT-6.1 Sol (High) GDPval-AA | 51.0% |
| Artificial Analysis | GPT-6.1 Sol (High) CritPt | 30.0% |
| Artificial Analysis | GPT-6.1 Sol (High) SciCode | 55.8% |
| Artificial Analysis | GPT-6.1 Sol (High) Terminal-Bench 4.0 | 51.5% |
| Artificial Analysis | GPT-6.1 Sol (High) AA-Omniscience Accuracy | 60.4% |
| Artificial Analysis | GPT-6.1 Sol (High) AA-Omniscience Non-Hallucination Rate | 51.0% |
| Artificial Analysis | GPT-6.1 Sol (Low) Intelligence Index | 34.8 |
| Artificial Analysis | GPT-6.1 Sol (Low) HLE | 47.4% |
| Artificial Analysis | GPT-6.1 Sol (Low) AA-LCR | 84.0% |
| Artificial Analysis | GPT-6.1 Sol (Low) GDPval-AA | 41.1% |
| Artificial Analysis | GPT-6.1 Sol (Low) CritPt | 24.9% |
| Artificial Analysis | GPT-6.1 Sol (Low) SciCode | 53.2% |
| Artificial Analysis | GPT-6.1 Sol (Low) Terminal-Bench 4.0 | 30.8% |
| Artificial Analysis | GPT-6.1 Sol (Low) AA-Omniscience Accuracy | 58.6% |
| Artificial Analysis | GPT-6.1 Sol (Low) AA-Omniscience Non-Hallucination Rate | 50.1% |
| Design Arena | GPT-6.1 Sol Agents Arena Androidnative Elo | 1197 |
| Design Arena | GPT-6.1 Sol Agents Arena Blender3d Elo | 1275 |
| Design Arena | GPT-6.1 Sol Agents Arena Codetovideo Elo | 1190 |
| Design Arena | GPT-6.1 Sol Agents Arena Mobile Apps Elo | 1231 |
| Design Arena | GPT-6.1 Sol Agents Arena Pdf Elo | 1137 |
| Design Arena | GPT-6.1 Sol Agents Arena Spreadsheet Elo | 1284 |
| Design Arena | GPT-6.1 Sol Agents Arena Webapps Elo | 1265 |
| Design Arena | GPT-6.1 Sol Models Arena 3D Elo | 1425 |
| Design Arena | GPT-6.1 Sol Models Arena Code Categories Elo | 1360 |
| Design Arena | GPT-6.1 Sol Models Arena Data Visualization Elo | 1273 |
| Design Arena | GPT-6.1 Sol Models Arena Game Development Elo | 1407 |
| Design Arena | GPT-6.1 Sol Models Arena UI Component Elo | 1358 |
| Design Arena | GPT-6.1 Sol Models Arena Website Elo | 1315 |
| Vals AI | GPT-6.1 Sol Access to Justice Benchmark | 65.8% |
| Vals AI | GPT-6.1 Sol BioMysteryBench | 79.6% |
| Vals AI | GPT-6.1 Sol ClaimBench | 100.0% |
| Vals AI | GPT-6.1 Sol Code Migration v1.1 | 77.3% |
| Vals AI | GPT-6.1 Sol CyberBench v1.1 | 39.3% |
| Vals AI | GPT-6.1 Sol EMB v1.1 | 71.1% |
| Vals AI | GPT-6.1 Sol Finance Agent v2.1 | 61.8% |
| Vals AI | GPT-6.1 Sol Vals Finance Index | 55.8% |
| Vals AI | GPT-6.1 Sol Financial Coaching Bench | 68.5% |
| Vals AI | GPT-6.1 Sol HLAB-Vals-1.1 | 6.3% |
| Vals AI | GPT-6.1 Sol Immigration | 67.8% |
| Vals AI | GPT-6.1 Sol IOI | 96.9% |
| Vals AI | GPT-6.1 Sol Vals Legal Index | 68.7% |
| Vals AI | GPT-6.1 Sol Legal Research Bench | 38.5% |
| Vals AI | GPT-6.1 Sol MedCode | 48.8% |
| Vals AI | GPT-6.1 Sol MedScribe | 86.5% |
| Vals AI | GPT-6.1 Sol MysteryMechanism | 46.4% |
| Vals AI | GPT-6.1 Sol ProgramBench | 3.0% |
| Vals AI | GPT-6.1 Sol ProofBench v1.1 | 99.0% |
| Vals AI | GPT-6.1 Sol Public Benefits Bench v1.1 | 59.3% |
| Vals AI | GPT-6.1 Sol Robo-bench | 28.3% |
| Vals AI | GPT-6.1 Sol Vals RSI Index | 26.6% |
| Vals AI | GPT-6.1 Sol SAGE | 90.5% |
| Vals AI | GPT-6.1 Sol Vals Science Index | 59.6% |
| Vals AI | GPT-6.1 Sol SRE Bench | 50.8% |
| Vals AI | GPT-6.1 Sol SWE-bench Multimodal | 43.5% |
| Vals AI | GPT-6.1 Sol Tax Agent Bench | 21.8% |
| Vals AI | GPT-6.1 Sol Terminal-Bench 4.0 | 55.1% |
| Vals AI | GPT-6.1 Sol Terminal-Bench-Science | 52.9% |
| Vals AI | GPT-6.1 Sol Vals Index | 63.9% |
| Vals AI | GPT-6.1 Sol Vibe Code Bench v1.1 | 88.9% |
Apps
Public apps that send the most traffic to this model. Good signal for what real production workloads look like — and a hint at which use cases this model is best suited for.
Activity
Token volume and request traffic to this model over time.
API
Drop-in code to call this model. OpenRouter's API is OpenAI-compatible — most SDKs work by just swapping the base URL. The only thing that changes between models is the model slug below.
Available through EU in-region routing
OpenAI: GPT-6.1 Sol is available through EU in-region routing. Requests sent to eu.openrouter.ai are decrypted in the EU and routed only to shared provider endpoints in Europe (the EU/EEA, the UK, and Switzerland).
- Providers in Europe
- Azure
- Prices in Europe
- Azure: $2.20/M tokens input, $11/M tokens output
- Base URL
https://eu.openrouter.ai/api/v1- Plan
- Requires Business or Enterprise. Self-serve on Business: no contract, no monthly minimum. OpenRouter Business for EU in-region routing
Fails closed: if no shared provider endpoint in Europe is available, the request errors instead of leaving the region. Requests served by your own BYOK key go to your deployment’s region, which you control. In-region routing docs
Documentation
Guides, cookbooks, blog posts, and tools for building with OpenAI: GPT-6.1 Sol on OpenRouter.
Frequently asked questions
GPT-6.1 Sol is an upgrade to GPT-6 Sol from OpenAI, positioned below the flagship GPT-6 Astra in the GPT-6 series. It is suited for agentic coding, computer use, document-heavy professional work, and multi-step business workflow automation, and approaches Astra-level results on these tasks at a much lower cost.
The GPT-6.1 Sol documentation on OpenRouter includes the Reranking in RAG: How to Fix Bad Retrieval with a Reranker blog post and the How to Benchmark LLMs blog post. The quickstart covers API keys and your first request, and the API reference lists every parameter.
GPT-6.1 Sol costs $2.00/M input tokens and $10.00/M output tokens, with separate rates for Cache Read at $0.10/M tokens and Cache Write at $2.50/M tokens.
GPT-6.1 Sol has a 1,050,000 token context window. It supports up to 128,000 completion tokens.
Yes. GPT-6.1 Sol accepts tools and tool_choice for function calling. It also supports structured outputs via a JSON schema in response_format.
Yes. OpenAI caches prompts of 1024 tokens or more automatically, and GPT-6.1 Sol bills a cache write on each cached prompt whether or not the cached prefix is read again. To turn caching off for a request, set prompt_cache_options.mode to "explicit" at the request root and do not mark any content block with prompt_cache_breakpoint. Explicit mode disables OpenAI-managed breakpoints, so a request with none of your own has no cacheable prefix and is billed at the plain input rate. See the prompt caching guide.
GPT-6.1 Sol accepts files such as PDFs, images, and text as input and returns text.
GPT-6.1 Sol is served by 3 providers on OpenRouter: OpenAI, Amazon Bedrock, and Azure. Requests are routed to the best available provider, with automatic failover to the others, and you can pin or exclude providers with provider routing.
GPT-6.1 Sol was released on September 29, 2026.