GLM-5 vs Qwen3.5-397B-A17B
GLM-5 (2026) and Qwen3.5-397B-A17B (2026) are frontier-tier reasoning models from Zhipu AI and Alibaba. GLM-5 ships a 200k-token context window, while Qwen3.5-397B-A17B ships a 262k-token context window. On SWE-bench Verified, GLM-5 leads by 1.6 pts. On pricing, Qwen3.5-397B-A17B costs $0.39/1M 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.
Qwen3.5-397B-A17B is ~54% cheaper at $0.39/1M; pay for GLM-5 only for provider fit.
Decision scorecard
Local evidence first| Signal | GLM-5 | Qwen3.5-397B-A17B |
|---|---|---|
| Best for | reasoning-heavy apps, tool-calling agents, and provider-routed production | reasoning-heavy apps, multimodal apps, and tool-calling agents |
| Decision fit | Coding, RAG, and Agents | Coding, RAG, and Agents |
| Context window | 200k | 262k |
| Cheapest output | $2.08/1M tokens | $2.34/1M tokens |
| Provider routes | 7 tracked | 4 tracked |
| Shared benchmarks | SWE-bench Verified leader | 1 rows |
Decision tradeoffs
- GLM-5 leads the largest shared benchmark signal on SWE-bench Verified by 1.6 points.
- GLM-5 has the lower cheapest tracked output price at $2.08/1M tokens.
- GLM-5 has broader tracked provider coverage for fallback and procurement flexibility.
- Local decision data tags GLM-5 for Coding, RAG, and Agents.
- Qwen3.5-397B-A17B has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Qwen3.5-397B-A17B uniquely exposes Multimodal in local model data.
- Local decision data tags Qwen3.5-397B-A17B 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
Qwen3.5-397B-A17B
$897
Cheapest tracked route/tier: OpenRouter
Estimated monthly gap: $103. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on OpenRouter, Together AI, and Novita AI; start route-level A/B tests there.
- Qwen3.5-397B-A17B is $0.26/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Qwen3.5-397B-A17B adds Multimodal in local capability data.
- Provider overlap exists on OpenRouter, Together AI, and Novita AI; start route-level A/B tests there.
- GLM-5 is $0.26/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Multimodal before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-02-11 | 2026-02-16 |
| Context window | 200k | 262k |
| Parameters | 744B total, 40B active | 397B |
| Architecture | mixture of experts | MoE |
| License | MIT | Apache 2.0 |
| Knowledge cutoff | 2025-11 | - |
Pricing and availability
| Pricing attribute | GLM-5 | Qwen3.5-397B-A17B |
|---|---|---|
| Input price | $0.60/1M tokens | $0.39/1M tokens |
| Output price | $2.08/1M tokens | $2.34/1M tokens |
| Providers |
Capabilities
| Capability | GLM-5 | Qwen3.5-397B-A17B |
|---|---|---|
| Vision | No | No |
| Multimodal | No | Yes |
| 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 | Qwen3.5-397B-A17B |
|---|---|---|
| SWE-bench Verified | 77.8 | 76.2 |
Deep dive
On shared benchmark coverage, SWE-bench Verified has GLM-5 at 77.8 and Qwen3.5-397B-A17B at 76.2, with GLM-5 ahead by 1.6 points. The largest visible gap is 1.6 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 differs most on multimodal input: Qwen3.5-397B-A17B. Both models share reasoning mode, function calling, tool use, and structured outputs, 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 lists $0.60/1M input and $2.08/1M output tokens on the cheapest tracked provider, while Qwen3.5-397B-A17B lists $0.39/1M input and $2.34/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Qwen3.5-397B-A17B lower by about $0.07 per million blended tokens. Availability is 7 providers versus 4, so concentration risk also matters.
Choose GLM-5 when provider fit and broader provider choice are central to the workload. Choose Qwen3.5-397B-A17B 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 Qwen3.5-397B-A17B?
Qwen3.5-397B-A17B 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 Qwen3.5-397B-A17B?
Qwen3.5-397B-A17B is cheaper on tracked token pricing. GLM-5 costs $0.60/1M input and $2.08/1M output tokens. Qwen3.5-397B-A17B costs $0.39/1M input and $2.34/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is GLM-5 or Qwen3.5-397B-A17B open source?
GLM-5 is listed under MIT. Qwen3.5-397B-A17B 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 multimodal input, GLM-5 or Qwen3.5-397B-A17B?
Qwen3.5-397B-A17B 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.
Which is better for reasoning mode, GLM-5 or Qwen3.5-397B-A17B?
Both GLM-5 and Qwen3.5-397B-A17B 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.
Where can I run GLM-5 and Qwen3.5-397B-A17B?
GLM-5 is available on Fireworks AI, OpenRouter, Together AI, GCP Vertex AI, and NVIDIA NIM. Qwen3.5-397B-A17B is available on OpenRouter, Together AI, Alibaba Cloud PAI-EAS, and Novita AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-05-22. Data sourced from public model cards and provider documentation.