GLM-4.6V vs Qwen3.5 9B Base vs Qwen3 Coder Next
GLM-4.6V comes out ahead, 58 to 50 and 47 on our weighted score, though Qwen3.5 9B Base is 5% cheaper per token.
- Our pick
Z.ai (Zhipu)GLM-4.6V
58/100- ECI—
- Price$0.30 / $0.90
- Context128K
Alibaba (Qwen)Qwen3.5 9B Base
50/100- ECI—
- Price$0.30 / $0.807
- Context262K
- Alibaba (Qwen)
Qwen3 Coder Next
47/100- ECI—
- Price$0.20 / $1.20
- Context262K
GLM-4.6V is our pick
GLM-4.6V is the better all-round choice, scoring 58/100 against Qwen3.5 9B Base (50) and Qwen3 Coder Next (47). It leads on inputs & features. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest priceQwen3.5 9B BaseQwen3.5 9B Base $0.427 · GLM-4.6V $0.45 · Qwen3 Coder Next $0.45 per 1M tokens (3:1 blend)
- Longest contextQwen3.5 9B Base and Qwen3 Coder NextQwen3.5 9B Base 262,144 · Qwen3 Coder Next 262,144 · GLM-4.6V 128,000 tokens
- Widest inputsGLM-4.6V and Qwen3.5 9B BaseGLM-4.6V: Text, Images, Video · Qwen3.5 9B Base: Text, Images, Video · Qwen3 Coder Next: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | GLM-4.6V | Qwen3.5 9B Base | Qwen3 Coder Next |
|---|---|---|---|---|
| Price | 50% | 64 | 65 | 64 |
| Inputs & features | 30% | 70 | 35 | 25 |
| Context window | 20% | 24 | 37 | 37 |
| Overall | 100% | 58/100 | 50/100 | 47/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | GLM-4.6VZ.ai (Zhipu) | Qwen3.5 9B BaseAlibaba (Qwen) | Qwen3 Coder NextAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.30 | $0.30 | $0.20 (best) |
| Output | $0.90 | $0.807 (best) | $1.20 |
| Cached input | $0.05 | — | — |
| Blended (3:1) | $0.45 | $0.427 (best) | $0.45 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Z.AI API | Median of 1 providers | Median of 15 providers |
| Limits | |||
| Context window | 128,000 tokens | 262,144 tokens (best) | 262,144 tokens (best) |
| Max output | 32,768 tokens | 65,536 tokens (best) | 65,536 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | Yes | Yes | No |
| Reasoning | Yes | No | No |
| Tool calling | Yes | No | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | OpenApache-2.0 | Open |
| API model ID | glm-4.6v | — | — |
| API providers | 15 | 1 | 16 (best) |
| Released | Dec 8, 2025 | Feb 26, 2026 | Feb 3, 2026 |
| Knowledge cutoff | Apr 2025 | — | Sep 2025 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- GLM-4.6V$4.80
- Qwen3.5 9B Base$4.61
- Qwen3 Coder Next$4.40
Which should you choose?
Which is better: GLM-4.6V, Qwen3.5 9B Base or Qwen3 Coder Next?
GLM-4.6V is the better all-round choice, scoring 58/100 against Qwen3.5 9B Base (50) and Qwen3 Coder Next (47). It leads on inputs & features. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, GLM-4.6V, Qwen3.5 9B Base or Qwen3 Coder Next?
Qwen3.5 9B Base is cheaper at $0.30 input / $0.807 output per million tokens (median across 1 API provider). GLM-4.6V costs $0.30 input / $0.90 output per million tokens (official Z.AI API price); Qwen3 Coder Next costs $0.20 input / $1.20 output per million tokens (median across 15 API providers). At a typical mix of three input tokens to one output token, that is $0.427 per million tokens for Qwen3.5 9B Base versus $0.45 for GLM-4.6V (1.1× as much) and $0.45 for Qwen3 Coder Next (1.1× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. GLM-4.6V has not been scored yet, Qwen3.5 9B Base has not been scored yet and Qwen3 Coder Next has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for GLM-4.6V, Qwen3.5 9B Base and Qwen3 Coder Next yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Qwen3.5 9B Base does not support tool calling, which most coding agents need.
Which has the bigger context window?
Qwen3.5 9B Base and Qwen3 Coder Next have the largest context windows (262,144 and 262,144 tokens), against 128,000 for GLM-4.6V. Maximum output per response: GLM-4.6V up to 32,768, Qwen3.5 9B Base up to 65,536, Qwen3 Coder Next up to 65,536 tokens.
Which can read images, PDFs, audio or video?
GLM-4.6V accepts text, images and video; Qwen3.5 9B Base accepts text, images and video; Qwen3 Coder Next accepts text. GLM-4.6V handles the widest range of inputs.
Are any of these open source?
Yes, all three publish their weights (Apache-2.0), so you can self-host them.
Which is newer?
Qwen3.5 9B Base is the newest, released Feb 26, 2026. Qwen3 Coder Next came out Feb 3, 2026; GLM-4.6V came out Dec 8, 2025. Knowledge cutoff: GLM-4.6V Apr 2025, Qwen3 Coder Next Sep 2025.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Nov 2, 2026.
