GLM-5 9B vs Phi-4 Mini Flash Reasoning
GLM-5 9B (2026) and Phi-4 Mini Flash Reasoning (2025) are frontier-tier reasoning models from Zhipu AI and Microsoft Research. GLM-5 9B ships a 262k-token context window, while Phi-4 Mini Flash Reasoning 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.
GLM-5 9B is safer overall; choose Phi-4 Mini Flash Reasoning when provider fit matters.
Decision scorecard
Local evidence first| Signal | GLM-5 9B | Phi-4 Mini Flash Reasoning |
|---|---|---|
| Best for | reasoning-heavy apps and tool-calling agents | reasoning-heavy apps |
| Decision fit | RAG, Agents, and Long context | Long context |
| Context window | 262k | 128k |
| Cheapest output | - | - |
| Provider routes | 0 tracked | 1 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 Function calling and Tool use in local model data.
- Local decision data tags GLM-5 9B for RAG, Agents, and Long context.
- Phi-4 Mini Flash Reasoning has broader tracked provider coverage for fallback and procurement flexibility.
- Local decision data tags Phi-4 Mini Flash Reasoning for Long context.
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
Phi-4 Mini Flash Reasoning
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-5 9B and Phi-4 Mini Flash Reasoning; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Function calling and Tool use before moving production traffic.
- No overlapping tracked provider route is sourced for Phi-4 Mini Flash Reasoning and GLM-5 9B; plan for SDK, billing, or endpoint changes.
- GLM-5 9B adds Function calling and Tool use in local capability data.
Specs
Pricing and availability
| Pricing attribute | GLM-5 9B | Phi-4 Mini Flash Reasoning |
|---|---|---|
| Input price | - | - |
| Output price | - | - |
| Providers | - |
Pricing not yet sourced for either model.
Capabilities
| Capability | GLM-5 9B | Phi-4 Mini Flash Reasoning |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | Yes | Yes |
| 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 function calling: GLM-5 9B and tool use: GLM-5 9B. Both models share reasoning mode, 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 Phi-4 Mini Flash Reasoning 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-5 9B when long-context analysis and larger context windows are central to the workload. Choose Phi-4 Mini Flash Reasoning 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 Phi-4 Mini Flash Reasoning?
GLM-5 9B supports 262k tokens, while Phi-4 Mini Flash Reasoning 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-5 9B or Phi-4 Mini Flash Reasoning open source?
GLM-5 9B is listed under MIT. Phi-4 Mini Flash Reasoning is listed under MIT. 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 Phi-4 Mini Flash Reasoning?
Both GLM-5 9B and Phi-4 Mini Flash Reasoning expose reasoning mode. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.
Which is better for function calling, GLM-5 9B or Phi-4 Mini Flash Reasoning?
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 Phi-4 Mini Flash Reasoning?
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 Phi-4 Mini Flash Reasoning?
GLM-5 9B is available on the tracked providers still being sourced. Phi-4 Mini Flash Reasoning 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.