GLM-5 vs Qwen3.5-35B-A3B
GLM-5 (2026) and Qwen3.5-35B-A3B (2026) are frontier-tier reasoning models from Zhipu AI and Alibaba. GLM-5 ships a 200k-token context window, while Qwen3.5-35B-A3B ships a 262k-token context window. On MMLU PRO, GLM-5 leads by 0.7 pts. On pricing, Qwen3.5-35B-A3B costs $0.14/1M input tokens versus $0.60/1M 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.
Qwen3.5-35B-A3B is ~332% cheaper at $0.14/1M; pay for GLM-5 only for provider fit.
Decision scorecard
Local evidence first| Signal | GLM-5 | Qwen3.5-35B-A3B |
|---|---|---|
| Best for | reasoning-heavy apps, tool-calling agents, and provider-routed production | reasoning-heavy apps, tool-calling agents, and provider-routed production |
| Decision fit | Coding, RAG, and Agents | Coding, RAG, and Agents |
| Context window | 200k | 262k |
| Cheapest output | $2.08/1M tokens | $1/1M tokens |
| Provider routes | 7 tracked | 2 tracked |
| Shared benchmarks | MMLU PRO leader | 7 rows |
Decision tradeoffs
- GLM-5 holds a shared-benchmark lead on MMLU PRO, ahead by 0.7 points.
- GLM-5 has broader tracked provider coverage for fallback and procurement flexibility.
- Local decision data tags GLM-5 for Coding, RAG, and Agents.
- Qwen3.5-35B-A3B has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Qwen3.5-35B-A3B has the lower cheapest tracked output price at $1/1M tokens.
- Local decision data tags Qwen3.5-35B-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
$1,000
Cheapest tracked route/tier: OpenRouter
Qwen3.5-35B-A3B
$361
Cheapest tracked route/tier: OpenRouter
Estimated monthly gap: $639. 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.
- Qwen3.5-35B-A3B is $1.08/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Provider overlap exists on OpenRouter and Novita AI; start route-level A/B tests there.
- GLM-5 is $1.08/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-02-11 | 2026-02-24 |
| Context window | 200k | 262k |
| Parameters | 744B total, 40B active | 35B |
| Architecture | mixture of experts | mixture of experts |
| 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 | Qwen3.5-35B-A3B |
|---|---|---|
| Input price | $0.60/1M tokens | $0.14/1M tokens |
| Output price | $2.08/1M tokens | $1/1M tokens |
| Providers |
Capabilities
| Capability | GLM-5 | Qwen3.5-35B-A3B |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | Yes | Yes |
| Function calling | Yes | Yes |
| Tool use | Yes | Yes |
| Structured outputs | Yes | Yes |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | GLM-5 | Qwen3.5-35B-A3B |
|---|---|---|
| MMLU PRO | 86.0 | 85.3 |
| SWE-bench Verified | 77.8 | 69.2 |
| Google-Proof Q&A | 86.0 | 84.5 |
| LiveCodeBench | 81.9 | 74.6 |
| Humanity's Last Exam | 30.5 | 22.4 |
| SWE-rebench | 62.8 | 53.7 |
| τ-bench | 82.1 | 81.2 |
Deep dive
On shared benchmark coverage, MMLU PRO has GLM-5 at 86 and Qwen3.5-35B-A3B at 85.3, with GLM-5 ahead by 0.7 points; SWE-bench Verified has GLM-5 at 77.8 and Qwen3.5-35B-A3B at 69.2, with GLM-5 ahead by 8.6 points; Google-Proof Q&A has GLM-5 at 86 and Qwen3.5-35B-A3B at 84.5, with GLM-5 ahead by 1.5 points. The largest visible gap is 8.6 points on SWE-bench Verified, 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 is close: both models cover reasoning mode, function calling, tool use, and structured outputs. That makes context budget, benchmark fit, and provider maturity more important than a simple checklist. If your application depends on one integration detail, verify it against the provider route you plan to use, not just the base model listing.
For cost, GLM-5 lists $0.60/1M input and $2.08/1M output tokens on the cheapest tracked provider, while Qwen3.5-35B-A3B lists $0.14/1M input and $1/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Qwen3.5-35B-A3B lower by about $0.65 per million blended tokens. Availability is 7 providers versus 2, so concentration risk also matters.
Choose GLM-5 when provider fit and broader provider choice are central to the workload. Choose Qwen3.5-35B-A3B when long-context analysis, 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 or Qwen3.5-35B-A3B?
Qwen3.5-35B-A3B supports 262k 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.
Which is cheaper, GLM-5 or Qwen3.5-35B-A3B?
Qwen3.5-35B-A3B is cheaper on tracked token pricing. GLM-5 costs $0.60/1M input and $2.08/1M output tokens. Qwen3.5-35B-A3B costs $0.14/1M input and $1/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is GLM-5 or Qwen3.5-35B-A3B open source?
GLM-5 is listed under MIT. Qwen3.5-35B-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 reasoning mode, GLM-5 or Qwen3.5-35B-A3B?
Both GLM-5 and Qwen3.5-35B-A3B expose reasoning mode. 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 function calling, GLM-5 or Qwen3.5-35B-A3B?
Both GLM-5 and Qwen3.5-35B-A3B expose function calling. 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.
Where can I run GLM-5 and Qwen3.5-35B-A3B?
GLM-5 is available on Fireworks AI, OpenRouter, Together AI, GCP Vertex AI, and NVIDIA NIM. Qwen3.5-35B-A3B is available on OpenRouter and Novita AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-05-22. Data sourced from public model cards and provider documentation.