GLM-5 vs Qwen3.5-235B-A22B
GLM-5 (2026) and Qwen3.5-235B-A22B (2026) are frontier reasoning models from Zhipu AI and Alibaba. GLM-5 ships a 200k-token context window, while Qwen3.5-235B-A22B ships a 512k-token context window. On SWE-bench Pro, GLM-5 leads by 3.4 pts. 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.
Qwen3.5-235B-A22B is safer overall; choose GLM-5 when reasoning depth matters.
Specs
| Released | 2026-02-11 | 2026-02-24 |
| Context window | 200k | 512k |
| Parameters | 744B total, 40B active | 235B |
| Architecture | mixture of experts | MoE |
| License | MIT | Apache 2.0 |
| Knowledge cutoff | - | - |
Pricing and availability
| GLM-5 | Qwen3.5-235B-A22B | |
|---|---|---|
| Input price | $0.72/1M tokens | - |
| Output price | $2.3/1M tokens | - |
| Providers | - |
Capabilities
| GLM-5 | Qwen3.5-235B-A22B | |
|---|---|---|
| Vision | ||
| Multimodal | ||
| Reasoning | ||
| Function calling | ||
| Tool use | ||
| Structured outputs | ||
| Code execution |
Benchmarks
| Benchmark | GLM-5 | Qwen3.5-235B-A22B |
|---|---|---|
| SWE-bench Pro | 38.6 | 35.2 |
Deep dive
On shared benchmark coverage, SWE-bench Pro has GLM-5 at 38.6 and Qwen3.5-235B-A22B at 35.2, with GLM-5 ahead by 3.4 points. The largest visible gap is 3.4 points on SWE-bench Pro, 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 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.
Pricing coverage is uneven: GLM-5 has $0.72/1M input tokens and Qwen3.5-235B-A22B has no token price sourced yet. Provider availability is 5 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 reasoning depth and broader provider choice are central to the workload. Choose Qwen3.5-235B-A22B 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.
FAQ
Which has a larger context window, GLM-5 or Qwen3.5-235B-A22B?
Qwen3.5-235B-A22B supports 512k tokens, while GLM-5 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-5 or Qwen3.5-235B-A22B open source?
GLM-5 is listed under MIT. Qwen3.5-235B-A22B 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 reasoning mode, GLM-5 or Qwen3.5-235B-A22B?
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 Qwen3.5-235B-A22B?
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 Qwen3.5-235B-A22B?
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 Qwen3.5-235B-A22B?
GLM-5 is available on Fireworks AI, OpenRouter, Together AI, GCP Vertex AI, and NVIDIA NIM. Qwen3.5-235B-A22B 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: 2026-04-24. Data sourced from public model cards and provider documentation.