AI Rate CardQwen3-Coder 480B-A35B Instruct vs Qwen3 VL 30B A3B Thinking: API price and specs
Qwen: Qwen3 VL 30B A3B Thinking is 53% cheaper than Qwen3-Coder 480B-A35B Instruct on input price.
Qwen3-Coder 480B-A35B Instruct is 19% cheaper than Qwen: Qwen3 VL 30B A3B Thinking on output price.
Qwen: Qwen3 VL 30B A3B Thinking is 21% cheaper than Qwen3-Coder 480B-A35B Instruct on a 1M-in / 200k-out workload.
| Field | Qwen3-Coder 480B-A35B Instruct | Qwen: Qwen3 VL 30B A3B Thinking |
|---|---|---|
| Lowest input, per 1M | $0.22 +114% | $0.10 |
| Median input, per 1M | $0.36 +24.6% | $0.29 |
| Lowest output, per 1M | $0.80 | $0.99 +23.7% |
| Median output, per 1M | $1.58 +57.5% | $1.00 |
| Lowest unit price | — | — |
| Cost of 1M in + 200k out | $0.38 +26.3% | $0.30 |
| Context | 262K | 262K |
| Max output | 262K | 262K +0.1% |
| Providers | 23 | 6 +73.9% |
| Regions | EU, US | — |
| Accepts | audio, image, text, video | image, image/bmp, image/heic, image/jpeg, image/png, image/tiff, image/webp, text, video/mp4, video/quicktime, video/x-flv, video/x-matroska, video/x-ms-wmv, video/x-msvideo |
| Returns | text | text |
| Type | Text models | Text models |
| Free option | no | no |
| Cheapest provider | google-vertex | aihubmix |
Your own workload: how many tokens the model gets (input) and gives back (output) - for example, in a month. The "Cost" row of the table above is recalculated for these numbers, for each model.
Computed from current offers each time the page opens; the best value of a row is bold, the percent is how far behind the best.
Providers selling both
aihubmix, deepinfra, kilo, openrouter, qiniu-ai, siliconflow
Frequently asked questions
Which is cheaper, Qwen3-Coder 480B-A35B Instruct or Qwen: Qwen3 VL 30B A3B Thinking?
Qwen: Qwen3 VL 30B A3B Thinking is 53% cheaper than Qwen3-Coder 480B-A35B Instruct on input price. Qwen3-Coder 480B-A35B Instruct is 19% cheaper than Qwen: Qwen3 VL 30B A3B Thinking on output price. Qwen: Qwen3 VL 30B A3B Thinking is 21% cheaper than Qwen3-Coder 480B-A35B Instruct on a 1M-in / 200k-out workload.
Which has the larger context, Qwen3-Coder 480B-A35B Instruct or Qwen: Qwen3 VL 30B A3B Thinking?
Qwen3-Coder 480B-A35B Instruct: 262K tokens; Qwen: Qwen3 VL 30B A3B Thinking: 262K tokens.
Where can I use both Qwen3-Coder 480B-A35B Instruct and Qwen: Qwen3 VL 30B A3B Thinking?
aihubmix, deepinfra, kilo, openrouter, qiniu-ai, siliconflow