GLM 4.6V vs Magistral Small 2506
GLM 4.6V (2026) and Magistral Small 2506 (2025) are frontier reasoning models from Tsinghua Knowledge Engineering Group (THUDM) and MistralAI. GLM 4.6V ships a 128K-token context window, while Magistral Small 2506 ships a 128K-token context window. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing. The goal is to make the tradeoff clear before deeper testing.
GLM 4.6V is safer overall; choose Magistral Small 2506 when reasoning depth matters.
Decision scorecard
Local evidence first| Signal | GLM 4.6V | Magistral Small 2506 |
|---|---|---|
| Decision fit | RAG, Agents, and Long context | Long context |
| Context window | 128K | 128K |
| Cheapest output | - | - |
| Provider routes | 0 tracked | 1 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- GLM 4.6V uniquely exposes Vision, Multimodal, and Function calling in local model data.
- Local decision data tags GLM 4.6V for RAG, Agents, and Long context.
- Magistral Small 2506 has broader tracked provider coverage for fallback and procurement flexibility.
- 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 prices on this page.
GLM 4.6V
Unavailable
No complete token price in local provider data
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 GLM 4.6V 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 GLM 4.6V; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Reasoning before moving production traffic.
- GLM 4.6V adds Vision, Multimodal, and Function calling in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-02-01 | 2025-06-10 |
| Context window | 128K | 128K |
| Parameters | — | — |
| Architecture | decoder only | decoder only |
| License | Proprietary | 1 |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | GLM 4.6V | Magistral Small 2506 |
|---|---|---|
| Input price | - | - |
| Output price | - | - |
| Providers | - |
Pricing not yet sourced for either model.
Capabilities
| Capability | GLM 4.6V | Magistral Small 2506 |
|---|---|---|
| Vision | Yes | No |
| Multimodal | Yes | No |
| Reasoning | No | Yes |
| Function calling | Yes | No |
| Tool use | Yes | No |
| Structured outputs | No | No |
| Code execution | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on vision: GLM 4.6V, multimodal input: GLM 4.6V, reasoning mode: Magistral Small 2506, function calling: GLM 4.6V, and tool use: GLM 4.6V. 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: GLM 4.6V has no token price sourced yet and Magistral Small 2506 has no token price sourced yet. Provider availability is 0 tracked routes versus 1. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose GLM 4.6V when vision-heavy evaluation are central to the workload. Choose Magistral Small 2506 when reasoning depth 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, GLM 4.6V or Magistral Small 2506?
GLM 4.6V supports 128K 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 GLM 4.6V or Magistral Small 2506 open source?
GLM 4.6V is listed under Proprietary. Magistral Small 2506 is listed under 1. 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, GLM 4.6V or Magistral Small 2506?
GLM 4.6V 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, GLM 4.6V or Magistral Small 2506?
GLM 4.6V 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, GLM 4.6V 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 GLM 4.6V and Magistral Small 2506?
GLM 4.6V is available on the tracked providers still being sourced. Magistral Small 2506 is available on NVIDIA NIM. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-05-14. Data sourced from public model cards and provider documentation.