GLM 4.7 vs Mistral Magistral Small 2509
GLM 4.7 (2026) and Mistral Magistral Small 2509 (2025) are general-purpose language models from Tsinghua Knowledge Engineering Group (THUDM) and MistralAI. GLM 4.7 ships a 200K-token context window, while Mistral Magistral Small 2509 ships a not-yet-sourced context window. On pricing, Mistral Magistral Small 2509 costs $0.5/1M input tokens versus $0.6/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
GLM 4.7 is safer overall; choose Mistral Magistral Small 2509 when provider fit matters.
Decision scorecard
Local evidence first| Signal | GLM 4.7 | Mistral Magistral Small 2509 |
|---|---|---|
| Decision fit | Coding, RAG, and Agents | General |
| Context window | 200K | — |
| Cheapest output | $2.2/1M tokens | $1.5/1M tokens |
| Provider routes | 1 tracked | 1 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- GLM 4.7 has the larger context window for long prompts, retrieval packs, or transcript analysis.
- GLM 4.7 uniquely exposes Function calling, Tool use, and Structured outputs in local model data.
- Local decision data tags GLM 4.7 for Coding, RAG, and Agents.
- Mistral Magistral Small 2509 has the lower cheapest tracked output price at $1.5/1M tokens.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output prices on this page.
GLM 4.7
$1,030
Cheapest tracked route: Fireworks AI
Mistral Magistral Small 2509
$775
Cheapest tracked route: AWS Bedrock
Estimated monthly gap: $255. Batch, cache, and negotiated pricing are excluded from this local estimate.
Switch friction
- No overlapping tracked provider route is sourced for GLM 4.7 and Mistral Magistral Small 2509; plan for SDK, billing, or endpoint changes.
- Mistral Magistral Small 2509 is $0.7/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Function calling, Tool use, and Structured outputs before moving production traffic.
- No overlapping tracked provider route is sourced for Mistral Magistral Small 2509 and GLM 4.7; plan for SDK, billing, or endpoint changes.
- GLM 4.7 is $0.7/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- GLM 4.7 adds Function calling, Tool use, and Structured outputs in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-03-01 | 2025-09-01 |
| Context window | 200K | — |
| Parameters | — | — |
| Architecture | decoder only | - |
| License | Proprietary | Proprietary |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | GLM 4.7 | Mistral Magistral Small 2509 |
|---|---|---|
| Input price | $0.6/1M tokens | $0.5/1M tokens |
| Output price | $2.2/1M tokens | $1.5/1M tokens |
| Providers |
Capabilities
| Capability | GLM 4.7 | Mistral Magistral Small 2509 |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| Function calling | Yes | No |
| Tool use | Yes | No |
| Structured outputs | Yes | No |
| Code execution | Yes | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on function calling: GLM 4.7, tool use: GLM 4.7, structured outputs: GLM 4.7, and code execution: GLM 4.7. 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.
For cost, GLM 4.7 lists $0.6/1M input and $2.2/1M output tokens, while Mistral Magistral Small 2509 lists $0.5/1M input and $1.5/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Mistral Magistral Small 2509 lower by about $0.28 per million blended tokens. Availability is 1 providers versus 1, so concentration risk also matters.
Choose GLM 4.7 when coding workflow support are central to the workload. Choose Mistral Magistral Small 2509 when provider fit and lower input-token cost 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 is cheaper, GLM 4.7 or Mistral Magistral Small 2509?
Mistral Magistral Small 2509 is cheaper on tracked token pricing. GLM 4.7 costs $0.6/1M input and $2.2/1M output tokens. Mistral Magistral Small 2509 costs $0.5/1M input and $1.5/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is GLM 4.7 or Mistral Magistral Small 2509 open source?
GLM 4.7 is listed under Proprietary. Mistral Magistral Small 2509 is listed under Proprietary. 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 function calling, GLM 4.7 or Mistral Magistral Small 2509?
GLM 4.7 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.
Which is better for tool use, GLM 4.7 or Mistral Magistral Small 2509?
GLM 4.7 has the clearer documented tool use signal in this comparison. If tool use is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for structured outputs, GLM 4.7 or Mistral Magistral Small 2509?
GLM 4.7 has the clearer documented structured outputs signal in this comparison. If structured outputs is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run GLM 4.7 and Mistral Magistral Small 2509?
GLM 4.7 is available on Fireworks AI. Mistral Magistral Small 2509 is available on AWS Bedrock. Provider coverage can affect latency, region availability, compliance posture, and fallback options. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Continue comparing
Last reviewed: 2026-05-11. Data sourced from public model cards and provider documentation.