GPT-5.5 vs Mistral Large 2
GPT-5.5 (2026) and Mistral Large 2 (2025) are frontier reasoning models from OpenAI and MistralAI. GPT-5.5 ships a 1.05m-token context window, while Mistral Large 2 ships a 128k-token context window. On MMLU PRO, GPT-5.5 leads by 18.4 pts. On pricing, GPT-5.5 ranges from $5 to $8/1M input tokens by tier; Mistral Large 2 costs $0.48/1M input tokens. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
GPT-5.5 fits 8x more tokens; pick it for long-context work and Mistral Large 2 for tighter calls.
Decision scorecard
Local evidence first| Signal | GPT-5.5 | Mistral Large 2 |
|---|---|---|
| Best for | reasoning-heavy apps, multimodal apps, and tool-calling agents | multimodal apps, tool-calling agents, and provider-routed production |
| Decision fit | Coding, RAG, and Agents | Coding, RAG, and Agents |
| Context window | 1.05m | 128k |
| Cheapest output | $30/1M tokens | $2.40/1M tokens |
| Provider routes | 3 tracked | 4 tracked |
| Shared benchmarks | MMLU PRO leader | 4 rows |
Decision tradeoffs
- GPT-5.5 holds a shared-benchmark lead on MMLU PRO, ahead by 18.4 points.
- GPT-5.5 has the larger context window for long prompts, retrieval packs, or transcript analysis.
- GPT-5.5 uniquely exposes Reasoning and Code execution in local model data.
- Local decision data tags GPT-5.5 for Coding, RAG, and Agents.
- Mistral Large 2 has the lower cheapest tracked output price at $2.40/1M tokens.
- Mistral Large 2 has broader tracked provider coverage for fallback and procurement flexibility.
- Local decision data tags Mistral Large 2 for Coding, RAG, and Agents.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
GPT-5.5
$11,500
Cheapest tracked route/tier: OpenAI API 0-272K input tokens
Mistral Large 2
$984
Cheapest tracked route/tier: AWS Bedrock
Estimated monthly gap: $10,516. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- Mistral Large 2 is $27.60/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Reasoning and Code execution before moving production traffic.
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- GPT-5.5 is $27.60/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- GPT-5.5 adds Reasoning and Code execution in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-04-23 | 2025-11-25 |
| Context window | 1.05m | 128k |
| Parameters | — | 123B |
| Architecture | decoder only | decoder only |
| License | Proprietary | Mistral License |
| Openness | Proprietary | Open weights |
| Commercial use | Commercial use with conditions | Non-commercial only |
| Knowledge cutoff | 2025-12 | 2025-07 |
Pricing and availability
| Pricing attribute | GPT-5.5 | Mistral Large 2 |
|---|---|---|
| Input price |
| $0.48/1M tokens |
| Output price |
| $2.40/1M tokens |
| Providers |
Capabilities
| Capability | GPT-5.5 | Mistral Large 2 |
|---|---|---|
| Vision | Yes | Yes |
| Multimodal | Yes | Yes |
| Reasoning | Yes | No |
| Function calling | Yes | Yes |
| Tool use | Yes | Yes |
| Structured outputs | Yes | Yes |
| Code execution | Yes | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | GPT-5.5 | Mistral Large 2 |
|---|---|---|
| MMLU PRO | 88.1 | 69.7 |
| HumanEval | 94.2 | 84.8 |
| Chatbot Arena | 1488.0 | 1265.0 |
| Massive Multitask Language Understanding | 92.4 | 84.0 |
Deep dive
On shared benchmark coverage, MMLU PRO has GPT-5.5 at 88.1 and Mistral Large 2 at 69.7, with GPT-5.5 ahead by 18.4 points; HumanEval has GPT-5.5 at 94.2 and Mistral Large 2 at 84.8, with GPT-5.5 ahead by 9.4 points; Chatbot Arena has GPT-5.5 at 1488 and Mistral Large 2 at 1265, with GPT-5.5 ahead by 223 points. The largest visible gap is 223 points on Chatbot Arena, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.
The capability footprint differs most on reasoning mode: GPT-5.5 and code execution: GPT-5.5. Both models share vision, multimodal input, function calling, and tool use, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.
For cost, GPT-5.5 lists tiered pricing: 0-272K input tokens is $5/1M input and $30/1M output; 272K+ input tokens is $8/1M input and $36/1M output, while Mistral Large 2 lists $0.48/1M input and $2.40/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Mistral Large 2 lower by about $11.44 per million blended tokens. For tiered rows, this cheapest-track view can understate interactive or fast-lane spend, so compare the tier you will actually use. Availability is 3 providers versus 4, so concentration risk also matters.
Choose GPT-5.5 when coding workflow support and larger context windows are central to the workload. Choose Mistral Large 2 when vision-heavy evaluation, lower input-token cost, and broader provider choice are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.
FAQ
Which has a larger context window, GPT-5.5 or Mistral Large 2?
GPT-5.5 supports 1.05m tokens, while Mistral Large 2 supports 128k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, GPT-5.5 or Mistral Large 2?
GPT-5.5 lists tiered pricing: 0-272K input tokens is $5/1M input and $30/1M output; 272K+ input tokens is $8/1M input and $36/1M output. Mistral Large 2 lists $0.48/1M input and $2.40/1M output tokens on the cheapest tracked provider. Compare the tier you will actually use; cheap async pricing can overstate savings for interactive workflows. Provider discounts or batch pricing can still change the final bill.
Is GPT-5.5 or Mistral Large 2 open source?
GPT-5.5 is listed under Proprietary. Mistral Large 2 is listed under Mistral License. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Which is better for vision, GPT-5.5 or Mistral Large 2?
Both GPT-5.5 and Mistral Large 2 expose vision. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for multimodal input, GPT-5.5 or Mistral Large 2?
Both GPT-5.5 and Mistral Large 2 expose multimodal input. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Where can I run GPT-5.5 and Mistral Large 2?
GPT-5.5 is available on OpenAI API, OpenRouter, and Vercel AI Gateway. Mistral Large 2 is available on OpenRouter, IBM watsonx, AWS Bedrock, and Mistral AI Studio. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-06-08. Data sourced from public model cards and provider documentation.