GLM-5 vs Phi-3 Mini 4k
GLM-5 (2026) and Phi-3 Mini 4k (2024) are frontier reasoning models from Zhipu AI and Microsoft Research. GLM-5 ships a 200k-token context window, while Phi-3 Mini 4k ships a 4K-token context window. On pricing, Phi-3 Mini 4k costs $0.05/1M 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.
Phi-3 Mini 4k is ~1340% cheaper at $0.05/1M; pay for GLM-5 only for reasoning depth.
Specs
| Released | 2026-02-11 | 2024-04-23 |
| Context window | 200k | 4K |
| Parameters | 744B total, 40B active | 3.8B |
| Architecture | mixture of experts | decoder only |
| License | MIT | Open Source |
| Knowledge cutoff | - | - |
Pricing and availability
| GLM-5 | Phi-3 Mini 4k | |
|---|---|---|
| Input price | $0.72/1M tokens | $0.05/1M tokens |
| Output price | $2.3/1M tokens | $0.25/1M tokens |
| Providers |
Capabilities
| GLM-5 | Phi-3 Mini 4k | |
|---|---|---|
| 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 Phi-3 Mini 4k lists $0.05/1M input and $0.25/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Phi-3 Mini 4k lower by about $1.08 per million blended tokens. Availability is 5 providers versus 4, so concentration risk also matters.
Choose GLM-5 when reasoning depth, larger context windows, and broader provider choice are central to the workload. Choose Phi-3 Mini 4k when provider fit and lower input-token cost 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 Phi-3 Mini 4k?
GLM-5 supports 200k tokens, while Phi-3 Mini 4k supports 4K 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 Phi-3 Mini 4k?
Phi-3 Mini 4k is cheaper on tracked token pricing. GLM-5 costs $0.72/1M input and $2.3/1M output tokens. Phi-3 Mini 4k costs $0.05/1M input and $0.25/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is GLM-5 or Phi-3 Mini 4k open source?
GLM-5 is listed under MIT. Phi-3 Mini 4k is listed under Open Source. 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-3 Mini 4k?
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 Phi-3 Mini 4k?
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 Phi-3 Mini 4k?
GLM-5 is available on Fireworks AI, OpenRouter, Together AI, GCP Vertex AI, and NVIDIA NIM. Phi-3 Mini 4k is available on Microsoft Foundry, NVIDIA NIM, Baseten API, and Replicate 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.