LLM Reference

GPT-5.3-Codex vs Mistral Large 2

GPT-5.3-Codex (2026) and Mistral Large 2 (2025) compare a coding-specialized model against a standalone API model. GPT-5.3-Codex ships a 400k-token context window, while Mistral Large 2 ships a 128k-token context window. On pricing, Mistral Large 2 costs $0.48/1M input tokens versus $1.75/1M for the alternative. This page treats the result as workflow and deployment fit, not a universal model winner.

Treat this as a product-type comparison: GPT-5.3-Codex is coding-specialized model, while Mistral Large 2 is standalone API model. Choose based on workflow fit before reading any benchmark or price row as decisive.

Decision scorecard

Local evidence first
SignalGPT-5.3-CodexMistral Large 2
Product typeCoding-specialized modelStandalone API model
Best forcustom coding agents, code generation, and tool loopsmultimodal apps, tool-calling agents, and provider-routed production
Decision fitCoding, RAG, and AgentsCoding, RAG, and Agents
Context window400k128k
Cheapest output$14/1M tokens$2.40/1M tokens
Provider routes3 tracked4 tracked
Shared benchmarks0 rows0 rows

Decision tradeoffs

Choose GPT-5.3-Codex when...
  • GPT-5.3-Codex has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • GPT-5.3-Codex uniquely exposes Reasoning, Code execution, and Computer use in local model data.
  • Local decision data tags GPT-5.3-Codex for Coding, RAG, and Agents.
Choose Mistral Large 2 when...
  • 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.
  • Mistral Large 2 uniquely exposes Multimodal in local model data.
  • 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.

Lower estimate Mistral Large 2

GPT-5.3-Codex

$4,900

Cheapest tracked route/tier: OpenRouter

Mistral Large 2

$984

Cheapest tracked route/tier: AWS Bedrock

Estimated monthly gap: $3,916. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.

Switch friction

GPT-5.3-Codex -> Mistral Large 2
  • Provider overlap exists on OpenRouter; start route-level A/B tests there.
  • Mistral Large 2 is $11.60/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
  • Check replacement coverage for Reasoning, Code execution, and Computer use before moving production traffic.
  • Mistral Large 2 adds Multimodal in local capability data.
Mistral Large 2 -> GPT-5.3-Codex
  • Provider overlap exists on OpenRouter; start route-level A/B tests there.
  • GPT-5.3-Codex is $11.60/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
  • Check replacement coverage for Multimodal before moving production traffic.
  • GPT-5.3-Codex adds Reasoning, Code execution, and Computer use in local capability data.

Specs

Specification
Released2026-02-052025-11-25
Context window400k128k
Parameters123B
Architecturedecoder onlydecoder only
LicenseProprietaryMistral License
OpennessProprietaryOpen weights
Commercial useCommercial use with conditionsNon-commercial only
Knowledge cutoff2025-082025-07

Pricing and availability

Pricing attributeGPT-5.3-CodexMistral Large 2
Input price$1.75/1M tokens$0.48/1M tokens
Output price$14/1M tokens$2.40/1M tokens
Providers

Capabilities

CapabilityGPT-5.3-CodexMistral Large 2
VisionYesYes
MultimodalNoYes
ReasoningYesNo
Function callingYesYes
Tool useYesYes
Structured outputsYesYes
Code executionYesNo
IDE integrationNoNo
Computer useYesNo
Parallel agentsNoNo

Benchmarks

No shared benchmark rows are currently sourced for this pair.

Deep dive

The capability footprint differs most on multimodal input: Mistral Large 2, reasoning mode: GPT-5.3-Codex, and code execution: GPT-5.3-Codex. Both models share vision, function calling, tool use, and structured outputs, 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-5.3-Codex lists $1.75/1M input and $14/1M output tokens on the cheapest tracked provider, 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 $4.37 per million blended tokens. Availability is 3 providers versus 4, so concentration risk also matters.

Choose GPT-5.3-Codex 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. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions.

FAQ

Which has a larger context window, GPT-5.3-Codex or Mistral Large 2?

GPT-5.3-Codex supports 400k 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-5.3-Codex or Mistral Large 2?

Mistral Large 2 is cheaper on tracked token pricing. GPT-5.3-Codex costs $1.75/1M input and $14/1M output tokens. Mistral Large 2 costs $0.48/1M input and $2.40/1M output tokens. Provider discounts or batch pricing can still change the final bill.

Is GPT-5.3-Codex or Mistral Large 2 open source?

GPT-5.3-Codex 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-5.3-Codex or Mistral Large 2?

Both GPT-5.3-Codex 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-5.3-Codex or Mistral Large 2?

Mistral Large 2 has the clearer documented multimodal input signal in this comparison. If multimodal input is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Where can I run GPT-5.3-Codex and Mistral Large 2?

GPT-5.3-Codex is available on OpenRouter, OpenAI API, 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: 2026-06-10. Data sourced from public model cards and provider documentation.