GLM-4.6V vs Trinity Nano Preview vs Qwen3 Coder Next
GLM-4.6V comes out ahead, 52 to 36 and 25 on our weighted score.
- Our pick
Z.ai (Zhipu)GLM-4.6V
52/100- ECI—
- Price$0.30 / $0.90
- Context128K
Arcee AITrinity Nano Preview
25/100- ECI—
- Price—
- Context131K
Alibaba (Qwen)Qwen3 Coder Next
36/100- ECI—
- Price$0.20 / $1.20
- Context262K
GLM-4.6V is our pick
GLM-4.6V is the better all-round choice, scoring 52/100 against Qwen3 Coder Next (36) and Trinity Nano Preview (25). It leads on inputs & features. Qwen3 Coder Next wins on context window. The score weighs inputs & features 60%, context window 40%. 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 priceGLM-4.6V and Qwen3 Coder NextGLM-4.6V $0.45 · Qwen3 Coder Next $0.45 per 1M tokens (3:1 blend) · Trinity Nano Preview unpriced
- Longest contextQwen3 Coder NextQwen3 Coder Next 262,144 · Trinity Nano Preview 131,072 · GLM-4.6V 128,000 tokens
- Widest inputsGLM-4.6VGLM-4.6V: Text, Images, Video · Trinity Nano Preview: Text · Qwen3 Coder Next: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | GLM-4.6V | Trinity Nano Preview | Qwen3 Coder Next |
|---|---|---|---|---|
| Inputs & features | 60% | 70 | 25 | 35 |
| Context window | 40% | 24 | 24 | 37 |
| Overall | 100% | 52/100 | 25/100 | 36/100 |
Left out because at least one model lacks the data: capability and price. 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) | Trinity Nano PreviewArcee AI | Qwen3 Coder NextAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.30 | — | $0.20 (best) |
| Output | $0.90 (best) | — | $1.20 |
| Cached input | — | — | — |
| Blended (3:1) | $0.45 | — | $0.45 |
| Long-context rate | Same rate | — | Same rate |
| Price source | Official Z.AI API | — | Median of 11 providers |
| Limits | |||
| Context window | 128,000 tokens | 131,072 tokens | 262,144 tokens (best) |
| Max output | 32,768 tokens | 131,072 tokens (best) | 65,536 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | Yes | No | No |
| Reasoning | Yes | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | Yes |
| Availability | |||
| Weights | Open | OpenOpenMDW-1.1 | Open |
| API model ID | glm-4.6v | — | — |
| API providers | 10 | — | 11 (best) |
| Released | Dec 8, 2025 | Dec 1, 2025 | 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
- Trinity Nano Preview—
- Qwen3 Coder Next$4.40
Which should you choose?
Which is better: GLM-4.6V, Trinity Nano Preview or Qwen3 Coder Next?
GLM-4.6V is the better all-round choice, scoring 52/100 against Qwen3 Coder Next (36) and Trinity Nano Preview (25). It leads on inputs & features. Qwen3 Coder Next wins on context window. The score weighs inputs & features 60%, context window 40%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, GLM-4.6V, Trinity Nano Preview or Qwen3 Coder Next?
GLM-4.6V is cheaper at $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 11 API providers). At a typical mix of three input tokens to one output token, that is $0.45 per million tokens for GLM-4.6V versus $0.45 for Qwen3 Coder Next (1× as much). Trinity Nano Preview has no published per-token price.
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. GLM-4.6V has not been scored yet, Trinity Nano Preview 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, Trinity Nano Preview and Qwen3 Coder Next yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.
Which has the bigger context window?
Qwen3 Coder Next has the largest context window at 262,144 tokens, against 131,072 for Trinity Nano Preview and 128,000 for GLM-4.6V. Maximum output per response: GLM-4.6V up to 32,768, Trinity Nano Preview up to 131,072, Qwen3 Coder Next up to 65,536 tokens.
Which can read images, PDFs, audio or video?
GLM-4.6V accepts text, images and video; Trinity Nano Preview accepts text; 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 (OpenMDW-1.1), so you can self-host them.
Which is newer?
Qwen3 Coder Next is the newest, released Feb 3, 2026. GLM-4.6V came out Dec 8, 2025; Trinity Nano Preview came out Dec 1, 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 Oct 4, 2026.
