Qwen-VL OCR vs Qwen3-Next 80B-A3B Instruct vs Aya Expanse 32B
Too close to call on our weighted score (Qwen3-Next 80B-A3B Instruct 39, Qwen-VL OCR 36, Aya Expanse 32B 33). The right pick depends on what you value most.
Alibaba (Qwen)Qwen-VL OCR
36/100- ECI—
- Price$0.72 / $0.72
- Context34K
- Alibaba (Qwen)
Qwen3-Next 80B-A3B Instruct
39/100- ECI—
- Price$0.50 / $2.00
- Context131K
CohereAya Expanse 32B
33/100- ECI—
- Price$0.50 / $1.50
- Context128K
Too close to call
It is close. Our weighted score puts them within 3 points (Qwen3-Next 80B-A3B Instruct 39/100, Qwen-VL OCR 36/100, Aya Expanse 32B 33/100), so choose by what matters most for your work: Qwen-VL OCR on price and Qwen3-Next 80B-A3B Instruct for long inputs. 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 priceQwen-VL OCRQwen-VL OCR $0.72 · Aya Expanse 32B $0.75 · Qwen3-Next 80B-A3B Instruct $0.875 per 1M tokens (3:1 blend)
- Longest contextQwen3-Next 80B-A3B InstructQwen3-Next 80B-A3B Instruct 131,072 · Aya Expanse 32B 128,000 · Qwen-VL OCR 34,096 tokens
- Widest inputsQwen-VL OCRQwen-VL OCR: Text, Images · Qwen3-Next 80B-A3B Instruct: Text · Aya Expanse 32B: Text
- Self-hostingQwen3-Next 80B-A3B Instruct and Aya Expanse 32BPublishes downloadable weights (CC-BY-NC-4.0)
| Measure | Weight | Qwen-VL OCR | Qwen3-Next 80B-A3B Instruct | Aya Expanse 32B |
|---|---|---|---|---|
| Price | 50% | 57 | 53 | 56 |
| Inputs & features | 30% | 25 | 25 | 0 |
| Context window | 20% | 1 | 24 | 24 |
| Overall | 100% | 36/100 | 39/100 | 33/100 |
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 | Qwen-VL OCRAlibaba (Qwen) | Qwen3-Next 80B-A3B InstructAlibaba (Qwen) | Aya Expanse 32BCohere |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.72 | $0.50 (best) | $0.50 (best) |
| Output | $0.72 (best) | $2.00 | $1.50 |
| Cached input | — | — | — |
| Blended (3:1) | $0.72 (best) | $0.875 | $0.75 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Alibaba API | Official Alibaba API | Median of 1 providers |
| Limits | |||
| Context window | 34,096 tokens | 131,072 tokens (best) | 128,000 tokens |
| Max output | 4,096 tokens | 32,768 tokens (best) | 4,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | No |
| Tool calling | No | Yes | No |
| Structured output | No | No | No |
| Availability | |||
| Weights | Proprietary | Open | OpenCC-BY-NC-4.0 |
| API model ID | qwen-vl-ocr | qwen3-next-80b-a3b-instruct | c4ai-aya-expanse-32b |
| API providers | 1 | 13 (best) | 2 |
| Released | Oct 28, 2024 | Sep 2025 | Oct 24, 2024 |
| Knowledge cutoff | Apr 2024 | Apr 2025 | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Qwen-VL OCR$8.64
- Qwen3-Next 80B-A3B Instruct$9.00
- Aya Expanse 32B$8.00
Which should you choose?
Which is better: Qwen-VL OCR, Qwen3-Next 80B-A3B Instruct or Aya Expanse 32B?
It is close. Our weighted score puts them within 3 points (Qwen3-Next 80B-A3B Instruct 39/100, Qwen-VL OCR 36/100, Aya Expanse 32B 33/100), so choose by what matters most for your work: Qwen-VL OCR on price and Qwen3-Next 80B-A3B Instruct for long inputs. 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, Qwen-VL OCR, Qwen3-Next 80B-A3B Instruct or Aya Expanse 32B?
Qwen-VL OCR is cheaper at $0.72 input / $0.72 output per million tokens (official Alibaba API price). Aya Expanse 32B costs $0.50 input / $1.50 output per million tokens (median across 1 API provider); Qwen3-Next 80B-A3B Instruct costs $0.50 input / $2.00 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $0.72 per million tokens for Qwen-VL OCR versus $0.75 for Aya Expanse 32B (1× as much) and $0.875 for Qwen3-Next 80B-A3B Instruct (1.2× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Qwen-VL OCR has not been scored yet, Qwen3-Next 80B-A3B Instruct has not been scored yet and Aya Expanse 32B has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen-VL OCR, Qwen3-Next 80B-A3B Instruct and Aya Expanse 32B yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Qwen-VL OCR and Aya Expanse 32B does not support tool calling, which most coding agents need.
Which has the bigger context window?
Qwen3-Next 80B-A3B Instruct has the largest context window at 131,072 tokens, against 128,000 for Aya Expanse 32B and 34,096 for Qwen-VL OCR. Maximum output per response: Qwen-VL OCR up to 4,096, Qwen3-Next 80B-A3B Instruct up to 32,768, Aya Expanse 32B up to 4,000 tokens.
Which can read images, PDFs, audio or video?
Qwen-VL OCR accepts text and images; Qwen3-Next 80B-A3B Instruct accepts text; Aya Expanse 32B accepts text. Qwen-VL OCR handles the widest range of inputs.
Are any of these open source?
Qwen3-Next 80B-A3B Instruct and Aya Expanse 32B publishes its weights (CC-BY-NC-4.0) and can be self-hosted; Qwen-VL OCR is proprietary.
Which is newer?
Qwen3-Next 80B-A3B Instruct is the newest, released Sep 2025. Qwen-VL OCR came out Oct 28, 2024; Aya Expanse 32B came out Oct 24, 2024. Knowledge cutoff: Qwen-VL OCR Apr 2024, Qwen3-Next 80B-A3B Instruct Apr 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.
