GLM-5.1 vs Qwen3.6-35B-A3B
GLM-5.1 (2026) and Qwen3.6-35B-A3B (2026) compare a standalone API model against a coding-specialized model. GLM-5.1 ships a 200k-token context window, while Qwen3.6-35B-A3B ships a 262k-token context window. On SWE-bench Pro, GLM-5.1 leads by 8.9 pts. On pricing, Qwen3.6-35B-A3B costs $0.15/1M input tokens versus $0.98/1M for the alternative. This page treats the result as workflow and deployment fit, not a universal model winner.
Treat this as a product-type comparison: GLM-5.1 is standalone API model, while Qwen3.6-35B-A3B is coding-specialized model. Choose based on workflow fit before reading any benchmark or price row as decisive.
Decision scorecard
Local evidence first| Signal | GLM-5.1 | Qwen3.6-35B-A3B |
|---|---|---|
| Product type | Standalone API model | Coding-specialized model |
| Best for | reasoning-heavy apps, tool-calling agents, and provider-routed production | custom coding agents, code generation, and tool loops |
| Decision fit | Coding, RAG, and Agents | Coding, RAG, and Agents |
| Context window | 200k | 262k |
| Cheapest output | $3.08/1M tokens | $1/1M tokens |
| Provider routes | 5 tracked | 2 tracked |
| Shared benchmarks | SWE-bench Pro leader | 2 rows |
Decision tradeoffs
- GLM-5.1 holds a shared-benchmark lead on SWE-bench Pro, ahead by 8.9 points.
- GLM-5.1 has broader tracked provider coverage for fallback and procurement flexibility.
- GLM-5.1 uniquely exposes Reasoning, Structured outputs, and Code execution in local model data.
- Local decision data tags GLM-5.1 for Coding, RAG, and Agents.
- Qwen3.6-35B-A3B has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Qwen3.6-35B-A3B has the lower cheapest tracked output price at $1/1M tokens.
- Qwen3.6-35B-A3B uniquely exposes Vision and Multimodal in local model data.
- Local decision data tags Qwen3.6-35B-A3B for Coding, RAG, and Agents.
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
Qwen3.6-35B-A3B
$370
Cheapest tracked route/tier: OpenRouter
Estimated monthly gap: $1,184. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on OpenRouter and Novita AI; start route-level A/B tests there.
- Qwen3.6-35B-A3B is $2.08/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Reasoning, Structured outputs, and Code execution before moving production traffic.
- Qwen3.6-35B-A3B adds Vision and Multimodal in local capability data.
- Provider overlap exists on OpenRouter and Novita AI; start route-level A/B tests there.
- GLM-5.1 is $2.08/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for Vision and Multimodal before moving production traffic.
- GLM-5.1 adds Reasoning, Structured outputs, and Code execution in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-04-07 | 2026-04-16 |
| Context window | 200k | 262k |
| Parameters | 754B total, 40B active | 35B |
| Architecture | mixture of experts | moe |
| License | MIT(OSI) | Apache 2.0(OSI) |
| Openness | Open source | Open source |
| Commercial use | Commercial use allowed | Commercial use allowed |
| Knowledge cutoff | 2025-11 | - |
Pricing and availability
| Pricing attribute | GLM-5.1 | Qwen3.6-35B-A3B |
|---|---|---|
| Input price | $0.98/1M tokens | $0.15/1M tokens |
| Output price | $3.08/1M tokens | $1/1M tokens |
| Providers |
Capabilities
| Capability | GLM-5.1 | Qwen3.6-35B-A3B |
|---|---|---|
| Vision | No | Yes |
| Multimodal | No | Yes |
| Reasoning | Yes | No |
| Function calling | Yes | Yes |
| Tool use | Yes | Yes |
| Structured outputs | Yes | No |
| Code execution | Yes | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | GLM-5.1 | Qwen3.6-35B-A3B |
|---|---|---|
| SWE-bench Pro | 58.4 | 49.5 |
| Google-Proof Q&A | 86.2 | 86.0 |
Deep dive
On shared benchmark coverage, SWE-bench Pro has GLM-5.1 at 58.4 and Qwen3.6-35B-A3B at 49.5, with GLM-5.1 ahead by 8.9 points; Google-Proof Q&A has GLM-5.1 at 86.2 and Qwen3.6-35B-A3B at 86, with GLM-5.1 ahead by 0.2 points. The largest visible gap is 8.9 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 vision: Qwen3.6-35B-A3B, multimodal input: Qwen3.6-35B-A3B, reasoning mode: GLM-5.1, structured outputs: GLM-5.1, and code execution: GLM-5.1. Both models share function calling and tool use, 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 Qwen3.6-35B-A3B lists $0.15/1M input and $1/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Qwen3.6-35B-A3B lower by about $1.20 per million blended tokens. Availability is 5 providers versus 2, so concentration risk also matters.
Choose GLM-5.1 when coding workflow support and broader provider choice are central to the workload. Choose Qwen3.6-35B-A3B when coding workflow support, larger context windows, 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.
FAQ
Which has a larger context window, GLM-5.1 or Qwen3.6-35B-A3B?
Qwen3.6-35B-A3B supports 262k tokens, while GLM-5.1 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.
Which is cheaper, GLM-5.1 or Qwen3.6-35B-A3B?
Qwen3.6-35B-A3B is cheaper on tracked token pricing. GLM-5.1 costs $0.98/1M input and $3.08/1M output tokens. Qwen3.6-35B-A3B costs $0.15/1M input and $1/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is GLM-5.1 or Qwen3.6-35B-A3B open source?
GLM-5.1 is listed under MIT. Qwen3.6-35B-A3B 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-5.1 or Qwen3.6-35B-A3B?
Qwen3.6-35B-A3B 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-5.1 or Qwen3.6-35B-A3B?
Qwen3.6-35B-A3B 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-5.1 and Qwen3.6-35B-A3B?
GLM-5.1 is available on Z.ai, OpenRouter, Fireworks AI, Vercel AI Gateway, and Novita AI. Qwen3.6-35B-A3B is available on OpenRouter and Novita AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-06-04. Data sourced from public model cards and provider documentation.