GPT-4 vs Magistral Small 2506
GPT-4 (2023) and Magistral Small 2506 (2025) are frontier reasoning models from OpenAI and MistralAI. GPT-4 ships a 8k-token context window, while Magistral Small 2506 ships a 128k-token context window. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads. It focuses on practical selection signals rather than broad model-family marketing.
Magistral Small 2506 fits 16x more tokens; pick it for long-context work and GPT-4 for tighter calls.
Decision scorecard
Local evidence first| Signal | GPT-4 | Magistral Small 2506 |
|---|---|---|
| Best for | multimodal apps, tool-calling agents, and provider-routed production | reasoning-heavy apps |
| Decision fit | Coding, Agents, and Vision | Long context |
| Context window | 8k | 128k |
| Cheapest output | $60/1M tokens | - |
| Provider routes | 4 tracked | 1 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- GPT-4 has broader tracked provider coverage for fallback and procurement flexibility.
- GPT-4 uniquely exposes Vision, Multimodal, and Function calling in local model data.
- Local decision data tags GPT-4 for Coding, Agents, and Vision.
- Magistral Small 2506 has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Magistral Small 2506 uniquely exposes Reasoning in local model data.
- 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-4
$39,000
Cheapest tracked route/tier: OpenAI API
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-4 and Magistral Small 2506; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Vision, Multimodal, and Function calling before moving production traffic.
- Magistral Small 2506 adds Reasoning in local capability data.
- No overlapping tracked provider route is sourced for Magistral Small 2506 and GPT-4; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Reasoning before moving production traffic.
- GPT-4 adds Vision, Multimodal, and Function calling in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2023-03-14 | 2025-06-10 |
| Context window | 8k | 128k |
| Parameters | 1.76T (8x222B MoE)* | 24B |
| Architecture | mixture of experts | decoder only |
| License | Proprietary | Apache 2.0(OSI) |
| Openness | Proprietary | Open source |
| Commercial use | Commercial use with conditions | Commercial use allowed |
| Knowledge cutoff | 2021-09 | 2025-06 |
Pricing and availability
| Pricing attribute | GPT-4 | Magistral Small 2506 |
|---|---|---|
| Input price | $30/1M tokens | - |
| Output price | $60/1M tokens | - |
| Providers |
Capabilities
| Capability | GPT-4 | Magistral Small 2506 |
|---|---|---|
| Vision | Yes | No |
| Multimodal | Yes | No |
| Reasoning | No | Yes |
| Function calling | Yes | No |
| Tool use | No | No |
| Structured outputs | Yes | No |
| Code execution | Yes | No |
| IDE integration | No | No |
| Computer use | No | 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-4, multimodal input: GPT-4, reasoning mode: Magistral Small 2506, function calling: GPT-4, structured outputs: GPT-4, and code execution: GPT-4. Both models share the core language-model surface, 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-4 has $30/1M input tokens and Magistral Small 2506 has no token price sourced yet. Provider availability is 4 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-4 when coding workflow support and broader provider choice are central to the workload. Choose Magistral Small 2506 when reasoning depth and larger context windows 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-4 or Magistral Small 2506?
Magistral Small 2506 supports 128k tokens, while GPT-4 supports 8k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Is GPT-4 or Magistral Small 2506 open source?
GPT-4 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-4 or Magistral Small 2506?
GPT-4 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 multimodal input, GPT-4 or Magistral Small 2506?
GPT-4 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 reasoning mode, GPT-4 or Magistral Small 2506?
Magistral Small 2506 has the clearer documented reasoning mode signal in this comparison. If reasoning mode is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run GPT-4 and Magistral Small 2506?
GPT-4 is available on OpenAI API, Azure OpenAI, Salesforce Einstein Generative AI, and OpenRouter. Magistral Small 2506 is available on NVIDIA NIM. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-05-22. Data sourced from public model cards and provider documentation.