GLM 4.6V vs Qwen3.5-9B
GLM 4.6V (2026) and Qwen3.5-9B (2026) are compact production models from Tsinghua Knowledge Engineering Group (THUDM) and Alibaba. GLM 4.6V ships a 128K-token context window, while Qwen3.5-9B 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.
Qwen3.5-9B is safer overall; choose GLM 4.6V when vision-heavy evaluation matters.
Decision scorecard
Local evidence first| Signal | GLM 4.6V | Qwen3.5-9B |
|---|---|---|
| Decision fit | RAG, Agents, and Long context | RAG, Agents, and Long context |
| Context window | 128K | 262K |
| Cheapest output | - | $0.15/1M tokens |
| Provider routes | 0 tracked | 3 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Local decision data tags GLM 4.6V for RAG, Agents, and Long context.
- Qwen3.5-9B has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Qwen3.5-9B has broader tracked provider coverage for fallback and procurement flexibility.
- Qwen3.5-9B uniquely exposes Structured outputs in local model data.
- Local decision data tags Qwen3.5-9B for RAG, Agents, and Long context.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output prices on this page.
GLM 4.6V
Unavailable
No complete token price in local provider data
Qwen3.5-9B
$118
Cheapest tracked route: Together AI
Cost delta unavailable until both models have sourced input and output token prices.
Switch friction
- No overlapping tracked provider route is sourced for GLM 4.6V and Qwen3.5-9B; plan for SDK, billing, or endpoint changes.
- Qwen3.5-9B adds Structured outputs in local capability data.
- No overlapping tracked provider route is sourced for Qwen3.5-9B and GLM 4.6V; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Structured outputs before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-02-01 | 2026-03-02 |
| Context window | 128K | 262K |
| Parameters | — | 9B |
| Architecture | decoder only | decoder only |
| License | Proprietary | Apache 2.0 |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | GLM 4.6V | Qwen3.5-9B |
|---|---|---|
| Input price | - | $0.1/1M tokens |
| Output price | - | $0.15/1M tokens |
| Providers | - |
Capabilities
| Capability | GLM 4.6V | Qwen3.5-9B |
|---|---|---|
| Vision | Yes | Yes |
| Multimodal | Yes | Yes |
| Reasoning | No | No |
| Function calling | Yes | Yes |
| Tool use | Yes | Yes |
| Structured outputs | No | Yes |
| Code execution | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on structured outputs: Qwen3.5-9B. Both models share vision, multimodal input, 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.
Pricing coverage is uneven: GLM 4.6V has no token price sourced yet and Qwen3.5-9B has $0.1/1M input tokens. Provider availability is 0 tracked routes versus 3. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose GLM 4.6V when vision-heavy evaluation are central to the workload. Choose Qwen3.5-9B when long-context analysis, larger context windows, and broader provider choice 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 4.6V or Qwen3.5-9B?
Qwen3.5-9B supports 262K tokens, while GLM 4.6V supports 128K 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 4.6V or Qwen3.5-9B open source?
GLM 4.6V is listed under Proprietary. Qwen3.5-9B 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 4.6V or Qwen3.5-9B?
Both GLM 4.6V and Qwen3.5-9B 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 4.6V or Qwen3.5-9B?
Both GLM 4.6V and Qwen3.5-9B 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 function calling, GLM 4.6V or Qwen3.5-9B?
Both GLM 4.6V and Qwen3.5-9B 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 4.6V and Qwen3.5-9B?
GLM 4.6V is available on the tracked providers still being sourced. Qwen3.5-9B is available on Together AI, OpenRouter, and Alibaba Cloud PAI-EAS. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-05-14. Data sourced from public model cards and provider documentation.