LLM Reference

GLM-5V-Turbo vs Qwen3.5-4B

GLM-5V-Turbo (2026) and Qwen3.5-4B (2026) are frontier reasoning models from Zhipu AI and Alibaba. GLM-5V-Turbo ships a 200k-token context window, while Qwen3.5-4B ships a 262k-token context window. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing. The goal is to make the tradeoff clear before deeper testing.

GLM-5V-Turbo is safer overall; choose Qwen3.5-4B when long-context analysis matters.

Decision scorecard

Local evidence first
SignalGLM-5V-TurboQwen3.5-4B
Best forreasoning-heavy apps, multimodal apps, and tool-calling agentsmultimodal apps
Decision fitRAG, Agents, and Long contextLong context and Vision
Context window200k262k
Cheapest output$4/1M tokens-
Provider routes2 tracked0 tracked
Shared benchmarks0 rows0 rows

Decision tradeoffs

Choose GLM-5V-Turbo when...
  • GLM-5V-Turbo has broader tracked provider coverage for fallback and procurement flexibility.
  • GLM-5V-Turbo uniquely exposes Reasoning, Function calling, and Tool use in local model data.
  • Local decision data tags GLM-5V-Turbo for RAG, Agents, and Long context.
Choose Qwen3.5-4B when...
  • Qwen3.5-4B has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Local decision data tags Qwen3.5-4B for Long context and Vision.

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

Qwen3.5-4B

Unavailable

No complete token price in local provider data

Cost delta unavailable until both models have sourced input and output token prices.

Switch friction

GLM-5V-Turbo -> Qwen3.5-4B
  • No overlapping tracked provider route is sourced for GLM-5V-Turbo and Qwen3.5-4B; plan for SDK, billing, or endpoint changes.
  • Check replacement coverage for Reasoning, Function calling, and Tool use before moving production traffic.
Qwen3.5-4B -> GLM-5V-Turbo
  • No overlapping tracked provider route is sourced for Qwen3.5-4B and GLM-5V-Turbo; plan for SDK, billing, or endpoint changes.
  • GLM-5V-Turbo adds Reasoning, Function calling, and Tool use in local capability data.

Specs

Specification
Released2026-04-012026-03-02
Context window200k262k
Parameters744B total, 40B active4B
Architecturemixture of experts-
LicenseProprietaryApache 2.0
Knowledge cutoff2025-11-

Pricing and availability

Pricing attributeGLM-5V-TurboQwen3.5-4B
Input price$1.20/1M tokens-
Output price$4/1M tokens-
Providers-

Capabilities

CapabilityGLM-5V-TurboQwen3.5-4B
VisionYesYes
MultimodalYesYes
ReasoningYesNo
Function callingYesNo
Tool useYesNo
Structured outputsYesNo
Code executionNoNo
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

No shared benchmark rows are currently sourced for this pair.

Deep dive

The capability footprint differs most on reasoning mode: GLM-5V-Turbo, function calling: GLM-5V-Turbo, tool use: GLM-5V-Turbo, and structured outputs: GLM-5V-Turbo. Both models share vision and multimodal input, 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-5V-Turbo has $1.20/1M input tokens and Qwen3.5-4B has no token price sourced yet. Provider availability is 2 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-5V-Turbo when reasoning depth and broader provider choice are central to the workload. Choose Qwen3.5-4B when long-context analysis and larger context windows 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-5V-Turbo or Qwen3.5-4B?

Qwen3.5-4B supports 262k tokens, while GLM-5V-Turbo supports 200k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.

Is GLM-5V-Turbo or Qwen3.5-4B open source?

GLM-5V-Turbo is listed under Proprietary. Qwen3.5-4B is listed under Apache 2.0. 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 Qwen3.5-4B?

Both GLM-5V-Turbo and Qwen3.5-4B expose vision. 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 multimodal input, GLM-5V-Turbo or Qwen3.5-4B?

Both GLM-5V-Turbo and Qwen3.5-4B expose multimodal input. 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 reasoning mode, GLM-5V-Turbo or Qwen3.5-4B?

GLM-5V-Turbo 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.

Where can I run GLM-5V-Turbo and Qwen3.5-4B?

GLM-5V-Turbo is available on OpenRouter and Vercel AI Gateway. Qwen3.5-4B 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.