GLM-5V-Turbo vs Phi 3.5 MoE Instruct
GLM-5V-Turbo (2026) and Phi 3.5 MoE Instruct (2024) are frontier reasoning models from Zhipu AI and Microsoft Research. GLM-5V-Turbo 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 $1.20/1M 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 ~140% cheaper at $0.50/1M; pay for GLM-5V-Turbo only for reasoning depth.
Decision scorecard
Local evidence first| Signal | GLM-5V-Turbo | Phi 3.5 MoE Instruct |
|---|---|---|
| Best for | reasoning-heavy apps, multimodal apps, and tool-calling agents | general production evaluation |
| Decision fit | RAG, Agents, and Long context | Long context |
| Context window | 200k | 128k |
| Cheapest output | $4/1M tokens | $0.50/1M tokens |
| Provider routes | 2 tracked | 1 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- GLM-5V-Turbo has the larger context window for long prompts, retrieval packs, or transcript analysis.
- GLM-5V-Turbo has broader tracked provider coverage for fallback and procurement flexibility.
- GLM-5V-Turbo uniquely exposes Vision, Multimodal, and Reasoning in local model data.
- Local decision data tags GLM-5V-Turbo for RAG, Agents, and Long context.
- 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-5V-Turbo
$1,960
Cheapest tracked route/tier: OpenRouter
Phi 3.5 MoE Instruct
$525
Cheapest tracked route/tier: Fireworks AI
Estimated monthly gap: $1,435. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- No overlapping tracked provider route is sourced for GLM-5V-Turbo and Phi 3.5 MoE Instruct; plan for SDK, billing, or endpoint changes.
- Phi 3.5 MoE Instruct is $3.50/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Vision, Multimodal, and Reasoning before moving production traffic.
- No overlapping tracked provider route is sourced for Phi 3.5 MoE Instruct and GLM-5V-Turbo; plan for SDK, billing, or endpoint changes.
- GLM-5V-Turbo is $3.50/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- GLM-5V-Turbo adds Vision, Multimodal, and Reasoning in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-04-01 | 2024-08-20 |
| Context window | 200k | 128k |
| Parameters | 744B 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-5V-Turbo | Phi 3.5 MoE Instruct |
|---|---|---|
| Input price | $1.20/1M tokens | $0.50/1M tokens |
| Output price | $4/1M tokens | $0.50/1M tokens |
| Providers |
Capabilities
| Capability | GLM-5V-Turbo | Phi 3.5 MoE Instruct |
|---|---|---|
| Vision | Yes | No |
| Multimodal | Yes | No |
| Reasoning | Yes | No |
| 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
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on vision: GLM-5V-Turbo, multimodal input: GLM-5V-Turbo, reasoning mode: GLM-5V-Turbo, function calling: GLM-5V-Turbo, tool use: GLM-5V-Turbo, and structured outputs: GLM-5V-Turbo. 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-5V-Turbo lists $1.20/1M input and $4/1M 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 $1.54 per million blended tokens. Availability is 2 providers versus 1, so concentration risk also matters.
Choose GLM-5V-Turbo when reasoning depth, 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-5V-Turbo or Phi 3.5 MoE Instruct?
GLM-5V-Turbo 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-5V-Turbo or Phi 3.5 MoE Instruct?
Phi 3.5 MoE Instruct is cheaper on tracked token pricing. GLM-5V-Turbo costs $1.20/1M input and $4/1M 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-5V-Turbo or Phi 3.5 MoE Instruct open source?
GLM-5V-Turbo 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 vision, GLM-5V-Turbo or Phi 3.5 MoE Instruct?
GLM-5V-Turbo has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for multimodal input, GLM-5V-Turbo or Phi 3.5 MoE Instruct?
GLM-5V-Turbo has the clearer documented multimodal input signal in this comparison. If multimodal input is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run GLM-5V-Turbo and Phi 3.5 MoE Instruct?
GLM-5V-Turbo is available on OpenRouter and Vercel AI Gateway. Phi 3.5 MoE Instruct is available on Fireworks AI. 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.