GLM-5 vs Phi-4 Mini Reasoning
GLM-5 (2026) and Phi-4 Mini Reasoning (2026) are frontier-tier reasoning models from Zhipu AI and Microsoft Research. GLM-5 ships a 200k-token context window, while Phi-4 Mini Reasoning ships a 128k-token context window. On Google-Proof Q&A, GLM-5 leads by 34 pts. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
Phi-4 Mini Reasoning is safer overall; choose GLM-5 when long-context analysis matters.
Decision scorecard
Local evidence first| Signal | GLM-5 | Phi-4 Mini Reasoning |
|---|---|---|
| Best for | reasoning-heavy apps, tool-calling agents, and provider-routed production | reasoning-heavy apps |
| Decision fit | Coding, RAG, and Agents | Long context |
| Context window | 200k | 128k |
| Cheapest output | $2.08/1M tokens | - |
| Provider routes | 7 tracked | 0 tracked |
| Shared benchmarks | Google-Proof Q&A leader | 1 rows |
Decision tradeoffs
- GLM-5 holds a shared-benchmark lead on Google-Proof Q&A, ahead by 34 points.
- GLM-5 has the larger context window for long prompts, retrieval packs, or transcript analysis.
- GLM-5 has broader tracked provider coverage for fallback and procurement flexibility.
- GLM-5 uniquely exposes Function calling, Tool use, and Structured outputs in local model data.
- Local decision data tags GLM-5 for Coding, RAG, and Agents.
- Local decision data tags Phi-4 Mini 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
$1,000
Cheapest tracked route/tier: OpenRouter
Phi-4 Mini 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 and Phi-4 Mini Reasoning; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Function calling, Tool use, and Structured outputs before moving production traffic.
- No overlapping tracked provider route is sourced for Phi-4 Mini Reasoning and GLM-5; plan for SDK, billing, or endpoint changes.
- GLM-5 adds Function calling, Tool use, and Structured outputs in local capability data.
Specs
Pricing and availability
| Pricing attribute | GLM-5 | Phi-4 Mini Reasoning |
|---|---|---|
| Input price | $0.60/1M tokens | - |
| Output price | $2.08/1M tokens | - |
| Providers | - |
Capabilities
| Capability | GLM-5 | Phi-4 Mini Reasoning |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | Yes | Yes |
| Function calling | Yes | No |
| Tool use | Yes | No |
| Structured outputs | Yes | No |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | GLM-5 | Phi-4 Mini Reasoning |
|---|---|---|
| Google-Proof Q&A | 86.0 | 52.0 |
Deep dive
On shared benchmark coverage, Google-Proof Q&A has GLM-5 at 86 and Phi-4 Mini Reasoning at 52, with GLM-5 ahead by 34 points. The largest visible gap is 34 points on Google-Proof Q&A, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.
The capability footprint differs most on function calling: GLM-5, tool use: GLM-5, and structured outputs: GLM-5. 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 has $0.60/1M input tokens and Phi-4 Mini Reasoning has no token price sourced yet. Provider availability is 7 tracked routes versus 0. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose GLM-5 when long-context analysis, larger context windows, and broader provider choice are central to the workload. Choose Phi-4 Mini Reasoning when provider fit are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.
FAQ
Which has a larger context window, GLM-5 or Phi-4 Mini Reasoning?
GLM-5 supports 200k tokens, while Phi-4 Mini 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 or Phi-4 Mini Reasoning open source?
GLM-5 is listed under MIT. Phi-4 Mini 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 or Phi-4 Mini Reasoning?
Both GLM-5 and Phi-4 Mini Reasoning expose reasoning mode. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for function calling, GLM-5 or Phi-4 Mini Reasoning?
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.
Which is better for tool use, GLM-5 or Phi-4 Mini Reasoning?
GLM-5 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 and Phi-4 Mini Reasoning?
GLM-5 is available on Fireworks AI, OpenRouter, Together AI, GCP Vertex AI, and NVIDIA NIM. Phi-4 Mini Reasoning is available on the tracked providers still being sourced. 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.