GLM-5 vs Mixtral 8x22B v0.1
GLM-5 (2026) and Mixtral 8x22B v0.1 (2024) are frontier reasoning models from Zhipu AI and MistralAI. GLM-5 ships a 200k-token context window, while Mixtral 8x22B v0.1 ships a 64K-token context window. On pricing, Mixtral 8x22B v0.1 costs $0.3/1M input tokens versus $0.72/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing.
Mixtral 8x22B v0.1 is ~140% cheaper at $0.3/1M; pay for GLM-5 only for reasoning depth.
Specs
| Released | 2026-02-11 | 2024-04-17 |
| Context window | 200k | 64K |
| Parameters | 744B total, 40B active | 8x22B |
| Architecture | mixture of experts | mixture of experts |
| License | MIT | Apache 2.0 |
| Knowledge cutoff | - | - |
Pricing and availability
| GLM-5 | Mixtral 8x22B v0.1 | |
|---|---|---|
| Input price | $0.72/1M tokens | $0.3/1M tokens |
| Output price | $2.3/1M tokens | $0.9/1M tokens |
| Providers |
Capabilities
| GLM-5 | Mixtral 8x22B v0.1 | |
|---|---|---|
| Vision | ||
| Multimodal | ||
| Reasoning | ||
| Function calling | ||
| Tool use | ||
| Structured outputs | ||
| Code execution |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on reasoning mode: GLM-5, function calling: GLM-5, tool use: GLM-5, and structured outputs: GLM-5. 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-5 lists $0.72/1M input and $2.3/1M output tokens, while Mixtral 8x22B v0.1 lists $0.3/1M input and $0.9/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Mixtral 8x22B v0.1 lower by about $0.71 per million blended tokens. Availability is 5 providers versus 8, so concentration risk also matters.
Choose GLM-5 when reasoning depth and larger context windows are central to the workload. Choose Mixtral 8x22B v0.1 when provider fit, lower input-token cost, 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-5 or Mixtral 8x22B v0.1?
GLM-5 supports 200k tokens, while Mixtral 8x22B v0.1 supports 64K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, GLM-5 or Mixtral 8x22B v0.1?
Mixtral 8x22B v0.1 is cheaper on tracked token pricing. GLM-5 costs $0.72/1M input and $2.3/1M output tokens. Mixtral 8x22B v0.1 costs $0.3/1M input and $0.9/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is GLM-5 or Mixtral 8x22B v0.1 open source?
GLM-5 is listed under MIT. Mixtral 8x22B v0.1 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 reasoning mode, GLM-5 or Mixtral 8x22B v0.1?
GLM-5 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.
Which is better for function calling, GLM-5 or Mixtral 8x22B v0.1?
GLM-5 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 GLM-5 and Mixtral 8x22B v0.1?
GLM-5 is available on Fireworks AI, OpenRouter, Together AI, GCP Vertex AI, and NVIDIA NIM. Mixtral 8x22B v0.1 is available on NVIDIA NIM, OctoAI API, Fireworks AI, DeepInfra, and Baseten API. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-04-24. Data sourced from public model cards and provider documentation.