GPT-5.3-Codex-Spark vs Mistral Large 3 675B Instruct
GPT-5.3-Codex-Spark (2026) and Mistral Large 3 675B Instruct (2025) compare a coding-specialized model against a standalone API model. GPT-5.3-Codex-Spark ships a 131k-token context window, while Mistral Large 3 675B Instruct ships a 128k-token context window. 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-Spark is coding-specialized model, while Mistral Large 3 675B Instruct is standalone API model. Choose based on workflow fit before reading any benchmark or price row as decisive.
Decision scorecard
Local evidence first| Signal | GPT-5.3-Codex-Spark | Mistral Large 3 675B Instruct |
|---|---|---|
| Product type | Coding-specialized model | Standalone API model |
| Best for | custom coding agents, code generation, and tool loops | multimodal apps and provider-routed production |
| Decision fit | Coding, RAG, and Agents | Coding, RAG, and Agents |
| Context window | 131k | 128k |
| Cheapest output | - | $1.50/1M tokens |
| Provider routes | 1 tracked | 6 tracked |
| Shared benchmarks | 0 shared | 0 shared |
Decision tradeoffs
- GPT-5.3-Codex-Spark has the larger context window for long prompts, retrieval packs, or transcript analysis.
- GPT-5.3-Codex-Spark uniquely exposes Function calling, Tool use, and Code execution in local model data.
- Local decision data tags GPT-5.3-Codex-Spark for Coding, RAG, and Agents.
- Mistral Large 3 675B Instruct has broader tracked provider coverage for fallback and procurement flexibility.
- Mistral Large 3 675B Instruct uniquely exposes Vision and Multimodal in local model data.
- Local decision data tags Mistral Large 3 675B Instruct 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-5.3-Codex-Spark
Unavailable
No complete token price in local provider data
Mistral Large 3 675B Instruct
$775
Cheapest tracked route/tier: OpenRouter
Cost delta unavailable until both models have sourced input and output token prices.
Switch friction
- No overlapping tracked provider route is sourced for GPT-5.3-Codex-Spark and Mistral Large 3 675B Instruct; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Function calling, Tool use, and Code execution before moving production traffic.
- Mistral Large 3 675B Instruct adds Vision and Multimodal in local capability data.
- No overlapping tracked provider route is sourced for Mistral Large 3 675B Instruct and GPT-5.3-Codex-Spark; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Vision and Multimodal before moving production traffic.
- GPT-5.3-Codex-Spark adds Function calling, Tool use, and Code execution in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-02-12 | 2025-12-01 |
| Context window | 131k | 128k |
| Parameters | — | 675B |
| Architecture | Decoder Only | Decoder Only |
| License | Proprietary | Apache 2.0OSI-approved |
| Openness | Proprietary | Open source |
| Commercial use | Commercial use: conditional | Commercial use: permitted |
| Knowledge cutoff | - | 2024-11 |
Pricing and availability
| Pricing attribute | GPT-5.3-Codex-Spark | Mistral Large 3 675B Instruct |
|---|---|---|
| Input price | - | $0.50/1M tokens |
| Output price | - | $1.50/1M tokens |
| Providers |
Capabilities
| Capability | GPT-5.3-Codex-Spark | Mistral Large 3 675B Instruct |
|---|---|---|
| Vision | No | Yes |
| Multimodal | No | Yes |
| Reasoning | No | No |
| Function calling | Yes | No |
| Tool use | Yes | No |
| Structured outputs | Yes | Yes |
| Code execution | Yes | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
No shared benchmark scores are currently available for this pair.
Deep dive
The capability footprint differs most on vision: Mistral Large 3 675B Instruct, multimodal input: Mistral Large 3 675B Instruct, function calling: GPT-5.3-Codex-Spark, tool use: GPT-5.3-Codex-Spark, and code execution: GPT-5.3-Codex-Spark. Both models share 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.
Pricing coverage is uneven: GPT-5.3-Codex-Spark has no token price sourced yet and Mistral Large 3 675B Instruct has $0.50/1M input tokens. Provider availability is 1 tracked routes versus 6. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose GPT-5.3-Codex-Spark when coding workflow support and larger context windows are central to the workload. Choose Mistral Large 3 675B Instruct when vision-heavy evaluation 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. It also helps separate model capability from provider packaging, which can change cost and latency.
FAQ
Which has a larger context window, GPT-5.3-Codex-Spark or Mistral Large 3 675B Instruct?
GPT-5.3-Codex-Spark supports 131k tokens, while Mistral Large 3 675B Instruct supports 128k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Is GPT-5.3-Codex-Spark or Mistral Large 3 675B Instruct open source?
GPT-5.3-Codex-Spark is listed under Proprietary. Mistral Large 3 675B Instruct is listed under Apache 2.0. 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-Spark or Mistral Large 3 675B Instruct?
Mistral Large 3 675B Instruct has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for multimodal input, GPT-5.3-Codex-Spark or Mistral Large 3 675B Instruct?
Mistral Large 3 675B Instruct 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.
Which is better for function calling, GPT-5.3-Codex-Spark or Mistral Large 3 675B Instruct?
GPT-5.3-Codex-Spark has the clearer documented function calling signal in this comparison. If function calling 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-Spark and Mistral Large 3 675B Instruct?
GPT-5.3-Codex-Spark is available on OpenAI API. Mistral Large 3 675B Instruct is available on OpenRouter, AWS Bedrock, NVIDIA NIM, Mistral AI Studio, and Microsoft Foundry. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-06-19. Data sourced from public model cards and provider documentation.