Model comparison
GPT-5.5 vs Mistral Large 3
OpenAI against Mistral, compared on context, price, and verified benchmark results.
Catalog record checked September 5, 2026Individual provider fields may changeEvidence confidence: High — see receipts below
OpenAI
GPT-5.5
Frontier
Mistral
Mistral Large 3
Frontier · Open weights
| Specification | GPT-5.5 | Mistral Large 3 |
|---|---|---|
| Provider | OpenAI | Mistral |
| Tier | Frontier | Frontier |
| Context window | Winner: 1.05M | 262K |
| Max output | 128K | Winner: 262K |
| Input / 1M tokens | $5 | Winner: $0.50 |
| Output / 1M tokens | $30 | Winner: $1.50 |
| Weights | Closed | Open |
| Parameters | Not disclosedUnverified | 675B total / 41B active (sparse MoE) |
| Reasoning levels | none, low, medium, high, xhigh, max | Not verifiedUnverified |
| Modalities | text, image | text, image |
| License | Not disclosedUnverified | Apache 2.0 |
| API model id | gpt-5.5 | mistral-large-3 |
| Released | April 23, 2026 | December 1, 2025 |
| Artificial Analysis Intelligence Index [xhigh] (2026-08-14) | 58 | Not verifiedUnverified |
| Artificial Analysis Intelligence Index (2026-08-14) | Not verifiedUnverified | 46 |
| SWE-bench Verified (2026-09-01) | 82.6 | Not verifiedUnverified |
| Terminal-Bench 2.1 (2026-07-27) | 83.4 | Not verifiedUnverified |
| GPQA Diamond (2026-07-27) | Winner: 93.5 | 43.9 |
| Humanity's Last Exam (2026-04-23) | 52.2 | Not verifiedUnverified |
Prices are USD per million tokens at standard rates, excluding batch and caching discounts. Bold indicates the better figure where one is objectively better. Values we could not confirm from the provider are shown as “Not verified” rather than estimated.
Benchmark receipts
- 2026-09-01: vals.ai SWE-bench Verified leaderboard (independent, mini-swe-agent bash-only); official SWE-bench not publishedReal GitHub issue resolution: does the model's patch pass the hidden tests. Comparability: comparable with caveat — Post-audit vendor claims and pre-audit scores sit on different task trust levels; scaffolding (agent harness, compute budget) also dominates results. Never aggregate across scaffolds.
- 2026-08-14: Artificial AnalysisComposite index blending reasoning, knowledge, and coding evals into one 0–100 score. Comparability: directly comparable — AA occasionally rebaselines the index scale between snapshots — a score captured on one date is only comparable to same-snapshot scores (check measuredAt).
- 2026-07-27: Kimi K3 model card (vendor-reported, xhigh); announcement charts show 93.6 — minor conflict preservedAgentic terminal work: multi-step tasks executed in a sandboxed shell environment. Comparability: comparable with caveat — Scores across Terminal-Bench major versions (v1 vs v2) are NOT comparable; harness configuration (container, time limits) also shifts results.
- 2026-04-23: OpenAI — Introducing GPT-5.5 (vendor, with tools; 41.4 no tools)Frontier-knowledge ceiling: extremely hard multi-domain questions written to be near-impossible without deep expertise. Comparability: comparable with caveat — Subset/tool configurations (text-only vs with-tools) differ between vendors and materially change scores; must match configuration to compare.
- 2025-12-02: Mistral — Introducing Mistral 3 (vendor, base model, 5-shot no CoT); independent review concursGraduate-level science reasoning: multiple-choice questions written by domain PhDs. Comparability: comparable with caveat — Small question pool: differences under ~2 points are within run-to-run noise. Chain-of-thought vs direct answering must match to compare.
Pricing tiers: GPT-5.5: Standard $5/$30 per MTok; >272K input billed 2x in / 1.5x out. Cached input $0.50/MTok; batch $2.50/$15. · Mistral Large 3: Mistral first-party API $0.50/$1.50 per MTok; cached input $0.05/MTok. Open weights (Apache 2.0), EU-hosted.
GPT-5.5
GPT-5.5 is OpenAI's previous flagship — strong on Terminal-Bench 2.0 (82.7%) and 1M-token context.
Best for
- Reasoning
- Agentic coding
- Long-context work
Watch out
Superseded by GPT-5.6 Sol on quality; still a capable, widely integrated model.
Mistral Large 3
Mistral Large 3 is Mistral's flagship — 262K-context, multimodal, Apache-2.0 open-weight at $0.50/$1.50.
Best for
- Open-weight deployments
- Multimodal EU-hosted inference
- Balanced frontier work
Watch out
Verify multimodal support and EU data-residency on your endpoint.
When the cheaper one wins
Mistral Large 3 is cheaper on output at $1.50 per million tokens against $30 for GPT-5.5 — about 20×. Use the cheaper tier for classification, extraction, summarisation, and any task where the expensive model’s extra score does not change the accepted output. The expensive one only pays if your hardest task actually fails on the cheap tier. These are standard-tier API rates, excluding batch and cache discounts.
Run the model pickerEvidence confidence: High
How strong and complete the evidence behind this comparison is — not a prediction of which model is better.
- Pricing verified on both sides — Input and output rates are verified for both models.
- 3/5 core specs verified on both sides — Not published for at least one side: parameter count, reasoning levels.
- 2 shared named benchmarks with differing scores — Measured on: Artificial Analysis Intelligence Index, GPQA Diamond.
- Verified within the last 90 days — Newest catalog check was 6 days ago.
- Both models carry source citations — Each side has at least two catalog sources on record.
Source receipts
Each catalog figure was checked against the provider or an independent second source on the date shown.
- GPT-5.5: OpenAI — Introducing GPT-5.5 (accessed 2026-08-29)
- GPT-5.5: OpenAI API pricing (gpt-5.5 $5/$30) (accessed 2026-08-29)
- Mistral Large 3: Mistral docs — mistral-large-2512 (675B total / 41B active, 256K) (accessed 2026-09-05)
- Mistral Large 3: Mistral — Introducing Mistral 3 (sparse MoE parameters) (accessed 2026-09-05)
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Diving deeper on one model? GPT-5.5 · Mistral Large 3
Common questions
GPT-5.5 vs Mistral Large 3
Answered from the verified figures on this page rather than general guidance.
Is GPT-5.5 or Mistral Large 3 cheaper for input?
Mistral Large 3 is cheaper at $0.50 per million input tokens, against $5 for GPT-5.5 — roughly 10× the price. Output tokens usually dominate a real bill, so weigh the output rate more heavily than the input rate. These are base rates; GPT-5.5 has tiered pricing: Standard $5/$30 per MTok; >272K input billed 2x in / 1.5x out. Cached input $0.50/MTok; batch $2.50/$15. Mistral Large 3 has tiered pricing: Mistral first-party API $0.50/$1.50 per MTok; cached input $0.05/MTok. Open weights (Apache 2.0), EU-hosted.
Is GPT-5.5 or Mistral Large 3 cheaper for output?
Mistral Large 3 is cheaper at $1.50 per million output tokens, against $30 for GPT-5.5 — roughly 20× the price. Output tokens usually dominate a real bill, so weigh the output rate more heavily than the input rate. These are base rates; GPT-5.5 has tiered pricing: Standard $5/$30 per MTok; >272K input billed 2x in / 1.5x out. Cached input $0.50/MTok; batch $2.50/$15. Mistral Large 3 has tiered pricing: Mistral first-party API $0.50/$1.50 per MTok; cached input $0.05/MTok. Open weights (Apache 2.0), EU-hosted.
Which has the larger context window, GPT-5.5 or Mistral Large 3?
GPT-5.5 accepts 1.05M tokens against 262K for Mistral Large 3. This only matters if you routinely send very long documents or large codebases.
Should I use GPT-5.5 or Mistral Large 3?
Both sit in the frontier tier, so the choice usually comes down to price and context rather than capability. GPT-5.5 suits reasoning; Mistral Large 3 suits open-weight deployments.
Can I self-host GPT-5.5 or Mistral Large 3?
Mistral Large 3 publishes open weights, but self-hosting and third-party provider access depend on the licence, hardware, serving support, and availability. GPT-5.5 is a closed model whose supported access paths are controlled by its provider.
Next step
Choosing between them
The verified figures that separate this pair, computed from the catalog rather than restated boilerplate.
- Input price: Mistral Large 3 costs $0.50 per 1M tokens versus $5 for GPT-5.5 — a 10x difference at the headline tier.
- Context: GPT-5.5 takes 1.05M against 262K for Mistral Large 3 — only decisive if your prompts approach the smaller window.
- Measured capability: GPT-5.5 leads Artificial Analysis Intelligence Index 58 to 46 (measured 2026-08-14).
- Deployment: Mistral Large 3 publishes weights you can self-host; the other is API-only.
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