GPT-5.3-Codex vs Magistral Small 2506
GPT-5.3-Codex (2026) and Magistral Small 2506 (2025) compare a coding-specialized model against a standalone API model. GPT-5.3-Codex ships a 400k-token context window, while Magistral Small 2506 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 is coding-specialized model, while Magistral Small 2506 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 | Magistral Small 2506 |
|---|---|---|
| Product type | Coding-specialized model | Standalone API model |
| Best for | custom coding agents, code generation, and tool loops | reasoning-heavy apps |
| Decision fit | Coding, RAG, and Agents | Long context |
| Context window | 400k | 128k |
| Cheapest output | $14/1M tokens | - |
| Provider routes | 3 tracked | 1 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- GPT-5.3-Codex has the larger context window for long prompts, retrieval packs, or transcript analysis.
- GPT-5.3-Codex has broader tracked provider coverage for fallback and procurement flexibility.
- GPT-5.3-Codex uniquely exposes Vision, Function calling, and Tool use in local model data.
- Local decision data tags GPT-5.3-Codex for Coding, RAG, and Agents.
- Local decision data tags Magistral Small 2506 for Long context.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
GPT-5.3-Codex
$4,900
Cheapest tracked route/tier: OpenRouter
Magistral Small 2506
Unavailable
No complete token price in local provider data
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 and Magistral Small 2506; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Vision, Function calling, and Tool use before moving production traffic.
- No overlapping tracked provider route is sourced for Magistral Small 2506 and GPT-5.3-Codex; plan for SDK, billing, or endpoint changes.
- GPT-5.3-Codex adds Vision, Function calling, and Tool use in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-02-05 | 2025-06-10 |
| Context window | 400k | 128k |
| Parameters | — | 24B |
| Architecture | decoder only | decoder only |
| License | Proprietary | Apache 2.0(OSI) |
| Openness | Proprietary | Open source |
| Commercial use | Commercial use with conditions | Commercial use allowed |
| Knowledge cutoff | 2025-08 | 2025-06 |
Pricing and availability
| Pricing attribute | GPT-5.3-Codex | Magistral Small 2506 |
|---|---|---|
| Input price | $1.75/1M tokens | - |
| Output price | $14/1M tokens | - |
| Providers |
Capabilities
| Capability | GPT-5.3-Codex | Magistral Small 2506 |
|---|---|---|
| Vision | Yes | No |
| Multimodal | No | No |
| Reasoning | Yes | Yes |
| Function calling | Yes | No |
| Tool use | Yes | No |
| Structured outputs | Yes | No |
| Code execution | Yes | No |
| IDE integration | No | No |
| Computer use | Yes | No |
| Parallel agents | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on vision: GPT-5.3-Codex, function calling: GPT-5.3-Codex, tool use: GPT-5.3-Codex, structured outputs: GPT-5.3-Codex, and code execution: GPT-5.3-Codex. Both models share reasoning mode, 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 has $1.75/1M input tokens and Magistral Small 2506 has no token price sourced yet. Provider availability is 3 tracked routes versus 1. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose GPT-5.3-Codex when coding workflow support, larger context windows, and broader provider choice are central to the workload. Choose Magistral Small 2506 when provider fit 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. For teams standardizing a stack, that distinction is often the difference between a benchmark win and a reliable deployment.
FAQ
Which has a larger context window, GPT-5.3-Codex or Magistral Small 2506?
GPT-5.3-Codex supports 400k tokens, while Magistral Small 2506 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 or Magistral Small 2506 open source?
GPT-5.3-Codex is listed under Proprietary. Magistral Small 2506 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 or Magistral Small 2506?
GPT-5.3-Codex 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. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for reasoning mode, GPT-5.3-Codex or Magistral Small 2506?
Both GPT-5.3-Codex and Magistral Small 2506 expose reasoning mode. 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 function calling, GPT-5.3-Codex or Magistral Small 2506?
GPT-5.3-Codex 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 and Magistral Small 2506?
GPT-5.3-Codex is available on OpenRouter, OpenAI API, and Vercel AI Gateway. Magistral Small 2506 is available on NVIDIA NIM. 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.