Qwen2.5-Coder-32B-Instruct vs Vision Small
Vision Small comes out ahead, 61 to 39 on our weighted score, though Qwen2.5-Coder-32B-Instruct is 2.1× cheaper per token.
Alibaba (Qwen)
Qwen2.5-Coder-32B-Instruct
39/100- ECI—
- Price$0.66 / $1.00
- Context131K
- Our pick
Vispark
Vision Small
61/100- ECI—
- Price$1.05 / $3.16
- Context1M
Add a model
Make it a three-way comparison.
Vision Small is our pick
Vision Small is the better all-round choice, scoring 61/100 against Qwen2.5-Coder-32B-Instruct (39). It leads on inputs & features and context window. Qwen2.5-Coder-32B-Instruct wins on price. 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 priceQwen2.5-Coder-32B-InstructQwen2.5-Coder-32B-Instruct $0.745 · Vision Small $1.58 per 1M tokens (3:1 blend)
- Longest contextVision SmallVision Small 1,000,000 · Qwen2.5-Coder-32B-Instruct 131,072 tokens
- Widest inputsVision SmallQwen2.5-Coder-32B-Instruct: Text · Vision Small: Text, Images, PDFs, Audio, Video
- Self-hostingQwen2.5-Coder-32B-InstructPublishes downloadable weights
| Measure | Weight | Qwen2.5-Coder-32B-Instruct | Vision Small |
|---|---|---|---|
| Price | 50% | 54 | 39 |
| Inputs & features | 30% | 25 | 100 |
| Context window | 20% | 25 | 60 |
| Overall | 100% | 39/100 | 61/100 |
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 | ||
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | $0.66 (best) | $1.05 |
| Output | $1.00 (best) | $3.16 |
| Cached input | — | — |
| Blended (3:1) | $0.745 (best) | $1.58 |
| Long-context rate | Same rate | Same rate |
| Price source | Median of 7 providers | Official Vispark API |
| Limits | ||
| Context window | 131,072 tokens | 1,000,000 tokens (best) |
| Max output | 8,192 tokens | 65,536 tokens (best) |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | Yes |
| PDFs | No | Yes |
| Audio | No | Yes |
| Video | No | Yes |
| Reasoning | No | Yes |
| Tool calling | Yes | Yes |
| Structured output | No | Yes |
| Availability | ||
| Weights | Open | Proprietary |
| API model ID | — | vispark/vision-small |
| API providers | 7 (best) | 1 |
| Released | Nov 12, 2024 | May 15, 2024 |
| Knowledge cutoff | — | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
Qwen2.5-Coder-32B-Instruct$8.60
Vision Small$16.82
Which should you choose?
Which is better: Qwen2.5-Coder-32B-Instruct or Vision Small?
Vision Small is the better all-round choice, scoring 61/100 against Qwen2.5-Coder-32B-Instruct (39). It leads on inputs & features and context window. Qwen2.5-Coder-32B-Instruct wins on price. 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, Qwen2.5-Coder-32B-Instruct or Vision Small?
Qwen2.5-Coder-32B-Instruct is cheaper at $0.66 input / $1.00 output per million tokens (median across 7 API providers). Vision Small costs $1.05 input / $3.16 output per million tokens (official Vispark API price). At a typical mix of three input tokens to one output token, that is $0.745 per million tokens for Qwen2.5-Coder-32B-Instruct versus $1.58 for Vision Small (2.1× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. Qwen2.5-Coder-32B-Instruct has not been scored yet and Vision Small has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen2.5-Coder-32B-Instruct and Vision Small yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Both support tool calling for agent workflows.
Which has the bigger context window?
Vision Small has the largest context window at 1,000,000 tokens, against 131,072 for Qwen2.5-Coder-32B-Instruct. Maximum output per response: Qwen2.5-Coder-32B-Instruct up to 8,192, Vision Small up to 65,536 tokens.
Which can read images, PDFs, audio or video?
Qwen2.5-Coder-32B-Instruct accepts text; Vision Small accepts text, images, PDFs, audio and video. Vision Small handles the widest range of inputs.
Are any of these open source?
Qwen2.5-Coder-32B-Instruct publishes its weights and can be self-hosted; Vision Small is proprietary.
Which is newer?
Qwen2.5-Coder-32B-Instruct is the newest, released Nov 12, 2024. Vision Small came out May 15, 2024.
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.