GLM-5.1 vs Phi 3.5 MoE Instruct
GLM-5.1 (2026) and Phi 3.5 MoE Instruct (2024) are frontier reasoning models from Zhipu AI and Microsoft Research. GLM-5.1 ships a 200k-token context window, while Phi 3.5 MoE Instruct ships a 128k-token context window. On pricing, Phi 3.5 MoE Instruct costs $0.50/1M input tokens versus $0.98/1M for the alternative. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
Phi 3.5 MoE Instruct is ~96% cheaper at $0.50/1M; pay for GLM-5.1 only for coding workflow support.
Decision scorecard
Local evidence first| Signal | GLM-5.1 | Phi 3.5 MoE Instruct |
|---|---|---|
| Best for | reasoning-heavy apps, tool-calling agents, and provider-routed production | general production evaluation |
| Decision fit | Coding, RAG, and Agents | Long context |
| Context window | 200k | 128k |
| Cheapest output | $3.08/1M tokens | $0.50/1M tokens |
| Provider routes | 5 tracked | 1 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- GLM-5.1 has the larger context window for long prompts, retrieval packs, or transcript analysis.
- GLM-5.1 has broader tracked provider coverage for fallback and procurement flexibility.
- GLM-5.1 uniquely exposes Reasoning, Function calling, and Tool use in local model data.
- Local decision data tags GLM-5.1 for Coding, RAG, and Agents.
- Phi 3.5 MoE Instruct has the lower cheapest tracked output price at $0.50/1M tokens.
- Local decision data tags Phi 3.5 MoE Instruct 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
$1,554
Cheapest tracked route/tier: Z.ai
Phi 3.5 MoE Instruct
$525
Cheapest tracked route/tier: Fireworks AI
Estimated monthly gap: $1,029. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on Fireworks AI; start route-level A/B tests there.
- Phi 3.5 MoE Instruct is $2.58/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Reasoning, Function calling, and Tool use before moving production traffic.
- Provider overlap exists on Fireworks AI; start route-level A/B tests there.
- GLM-5.1 is $2.58/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- GLM-5.1 adds Reasoning, Function calling, and Tool use in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-04-07 | 2024-08-20 |
| Context window | 200k | 128k |
| Parameters | 754B total, 40B active | 16x3.8B (42B, 6.6B active) |
| Architecture | mixture of experts | decoder only |
| License | MIT(OSI) | MIT(OSI) |
| Openness | Open source | Open source |
| Commercial use | Commercial use allowed | Commercial use allowed |
| Knowledge cutoff | 2025-11 | 2023-10 |
Pricing and availability
| Pricing attribute | GLM-5.1 | Phi 3.5 MoE Instruct |
|---|---|---|
| Input price | $0.98/1M tokens | $0.50/1M tokens |
| Output price | $3.08/1M tokens | $0.50/1M tokens |
| Providers |
Capabilities
| Capability | GLM-5.1 | Phi 3.5 MoE Instruct |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | Yes | No |
| Function calling | Yes | No |
| Tool use | Yes | No |
| Structured outputs | Yes | No |
| Code execution | Yes | 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-5.1, function calling: GLM-5.1, tool use: GLM-5.1, structured outputs: GLM-5.1, and code execution: GLM-5.1. 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-5.1 lists $0.98/1M input and $3.08/1M output tokens on the cheapest tracked provider, while Phi 3.5 MoE Instruct lists $0.50/1M input and $0.50/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Phi 3.5 MoE Instruct lower by about $1.11 per million blended tokens. Availability is 5 providers versus 1, so concentration risk also matters.
Choose GLM-5.1 when coding workflow support, larger context windows, and broader provider choice are central to the workload. Choose Phi 3.5 MoE Instruct 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.
FAQ
Which has a larger context window, GLM-5.1 or Phi 3.5 MoE Instruct?
GLM-5.1 supports 200k tokens, while Phi 3.5 MoE Instruct supports 128k 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-5.1 or Phi 3.5 MoE Instruct?
Phi 3.5 MoE Instruct is cheaper on tracked token pricing. GLM-5.1 costs $0.98/1M input and $3.08/1M output tokens. Phi 3.5 MoE Instruct costs $0.50/1M input and $0.50/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is GLM-5.1 or Phi 3.5 MoE Instruct open source?
GLM-5.1 is listed under MIT. Phi 3.5 MoE Instruct 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-5.1 or Phi 3.5 MoE Instruct?
GLM-5.1 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-5.1 or Phi 3.5 MoE Instruct?
GLM-5.1 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-5.1 and Phi 3.5 MoE Instruct?
GLM-5.1 is available on Z.ai, OpenRouter, Fireworks AI, Vercel AI Gateway, and Novita AI. Phi 3.5 MoE Instruct is available on Fireworks AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-05-25. Data sourced from public model cards and provider documentation.