Model comparison
GPT-5.3-Codex 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-5.3-Codex
Frontier
Mistral
Mistral Large 3
Frontier · Open weights
| Specification | GPT-5.3-Codex | Mistral Large 3 |
|---|---|---|
| Provider | OpenAI | Mistral |
| Tier | Frontier | Frontier |
| Context window | Winner: 400K | 262K |
| Max output | 128K | Winner: 262K |
| Input / 1M tokens | $1.75 | Winner: $0.50 |
| Output / 1M tokens | $14 | 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-5.3-codex | mistral-large-3 |
| Released | February 5, 2026 | December 1, 2025 |
| Artificial Analysis Intelligence Index [high] (2026-08-14) | 52 | Not verifiedUnverified |
| Artificial Analysis Intelligence Index (2026-08-14) | Not verifiedUnverified | 46 |
| GPQA Diamond (2025-12-02) | Not verifiedUnverified | 43.9 |
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
- 2026-08-14: 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).
- 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-5.3-Codex: Standard $1.75/$14 per MTok; cached input $0.175/MTok; Fast mode $3.50/$28. Purpose-built for the Codex agent. · 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-5.3-Codex
GPT-5.3-Codex is OpenAI's coding-specialised model powering the Codex agent at $1.75/$14.
Best for
- Autonomous coding
- Repo-scale refactors
- Test generation
Watch out
Tuned for coding, not general chat; use GPT-5.6 for broad reasoning.
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 $14 for GPT-5.3-Codex — about 9.3×. 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.
- 1 shared named benchmark with differing scores — Measured on: Artificial Analysis Intelligence Index.
- 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-5.3-Codex: OpenAI — Introducing GPT-5.3-Codex (accessed 2026-08-29)
- GPT-5.3-Codex: OpenAI API pricing (gpt-5.3-codex $1.75/$14) (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)
Related comparisons
- Claude Fable 5.1 vs GPT-5.3-Codex
- Claude Fable 5.1 vs Mistral Large 3
- Claude Fable 5 vs GPT-5.3-Codex
- Claude Fable 5 vs Mistral Large 3
- Claude Mythos 5.1 vs GPT-5.3-Codex
- Claude Mythos 5.1 vs Mistral Large 3
Diving deeper on one model? GPT-5.3-Codex · Mistral Large 3
Common questions
GPT-5.3-Codex vs Mistral Large 3
Answered from the verified figures on this page rather than general guidance.
Is GPT-5.3-Codex or Mistral Large 3 cheaper for input?
Mistral Large 3 is cheaper at $0.50 per million input tokens, against $1.75 for GPT-5.3-Codex — roughly 3.5× 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-5.3-Codex has tiered pricing: Standard $1.75/$14 per MTok; cached input $0.175/MTok; Fast mode $3.50/$28. Purpose-built for the Codex agent. 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-5.3-Codex or Mistral Large 3 cheaper for output?
Mistral Large 3 is cheaper at $1.50 per million output tokens, against $14 for GPT-5.3-Codex — roughly 9.3× 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-5.3-Codex has tiered pricing: Standard $1.75/$14 per MTok; cached input $0.175/MTok; Fast mode $3.50/$28. Purpose-built for the Codex agent. 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-5.3-Codex or Mistral Large 3?
GPT-5.3-Codex accepts 400K tokens against 262K for Mistral Large 3. This only matters if you routinely send very long documents or large codebases.
Should I use GPT-5.3-Codex or Mistral Large 3?
Both sit in the frontier tier, so the choice usually comes down to price and context rather than capability. GPT-5.3-Codex suits autonomous coding; Mistral Large 3 suits open-weight deployments.
Can I self-host GPT-5.3-Codex 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-5.3-Codex 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 $1.75 for GPT-5.3-Codex — a 3.5x difference at the headline tier.
- Context: GPT-5.3-Codex takes 400K against 262K for Mistral Large 3 — only decisive if your prompts approach the smaller window.
- Measured capability: GPT-5.3-Codex leads Artificial Analysis Intelligence Index 52 to 46 (measured 2026-08-14).
- Deployment: Mistral Large 3 publishes weights you can self-host; the other is API-only.
Choosing a harness rather than a model — Cursor, Copilot, Claude Code, Windsurf, or Lovable? Compare agentic harnesses · Latest releases.