GLM-5 9B vs Mixtral 8x7B
GLM-5 9B (2026) and Mixtral 8x7B (2023) are frontier reasoning models from Zhipu AI and MistralAI. GLM-5 9B ships a 262k-token context window, while Mixtral 8x7B ships a 32k-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.
GLM-5 9B fits 8x more tokens; pick it for long-context work and Mixtral 8x7B for tighter calls.
Decision scorecard
Local evidence first| Signal | GLM-5 9B | Mixtral 8x7B |
|---|---|---|
| Best for | reasoning-heavy apps and tool-calling agents | provider-routed production |
| Decision fit | RAG, Agents, and Long context | Coding and Classification |
| Context window | 262k | 32k |
| Cheapest output | - | $0.45/1M tokens |
| Provider routes | 0 tracked | 18 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- GLM-5 9B has the larger context window for long prompts, retrieval packs, or transcript analysis.
- GLM-5 9B uniquely exposes Reasoning, Function calling, and Tool use in local model data.
- Local decision data tags GLM-5 9B for RAG, Agents, and Long context.
- Mixtral 8x7B has broader tracked provider coverage for fallback and procurement flexibility.
- Local decision data tags Mixtral 8x7B for Coding and Classification.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
GLM-5 9B
Unavailable
No complete token price in local provider data
Mixtral 8x7B
$233
Cheapest tracked route/tier: Mistral AI Studio
Cost delta unavailable until both models have sourced input and output token prices.
Switch friction
- No overlapping tracked provider route is sourced for GLM-5 9B and Mixtral 8x7B; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Reasoning, Function calling, and Tool use before moving production traffic.
- No overlapping tracked provider route is sourced for Mixtral 8x7B and GLM-5 9B; plan for SDK, billing, or endpoint changes.
- GLM-5 9B adds Reasoning, Function calling, and Tool use in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-02-15 | 2023-12-11 |
| Context window | 262k | 32k |
| Parameters | 9 | 8x7B |
| Architecture | decoder only | mixture of experts |
| License | MIT(OSI) | Apache 2.0(OSI) |
| Openness | Open source | Open source |
| Commercial use | Commercial use allowed | Commercial use allowed |
| Knowledge cutoff | 2025-11 | 2023-12 |
Pricing and availability
| Pricing attribute | GLM-5 9B | Mixtral 8x7B |
|---|---|---|
| Input price | - | $0.15/1M tokens |
| Output price | - | $0.45/1M tokens |
| Providers | - |
Capabilities
| Capability | GLM-5 9B | Mixtral 8x7B |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | Yes | No |
| Function calling | Yes | No |
| Tool use | Yes | No |
| Structured outputs | No | No |
| Code execution | No | 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 reasoning mode: GLM-5 9B, function calling: GLM-5 9B, and tool use: GLM-5 9B. 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-5 9B has no token price sourced yet and Mixtral 8x7B has $0.15/1M input tokens. Provider availability is 0 tracked routes versus 18. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose GLM-5 9B when reasoning depth and larger context windows are central to the workload. Choose Mixtral 8x7B when provider fit 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. 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, GLM-5 9B or Mixtral 8x7B?
GLM-5 9B supports 262k tokens, while Mixtral 8x7B supports 32k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Is GLM-5 9B or Mixtral 8x7B open source?
GLM-5 9B is listed under MIT. Mixtral 8x7B 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 9B or Mixtral 8x7B?
GLM-5 9B 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 9B or Mixtral 8x7B?
GLM-5 9B 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-5 9B or Mixtral 8x7B?
GLM-5 9B 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.
Where can I run GLM-5 9B and Mixtral 8x7B?
GLM-5 9B is available on the tracked providers still being sourced. Mixtral 8x7B is available on Databricks Foundation Model Serving, NVIDIA NIM, GCP Vertex AI, AWS Bedrock, and OctoAI API (Deprecated). Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-05-16. Data sourced from public model cards and provider documentation.