Aya Expanse 32B vs Qwen2.5-Coder-32B-Instruct vs Solar Pro 2
Solar Pro 2 comes out ahead, 51 to 39 and 32 on our weighted score, and it is the cheaper option too.
CohereAya Expanse 32B
32/100- ECI—
- Price$0.50 / $1.50
- Context128K
Alibaba (Qwen)Qwen2.5-Coder-32B-Instruct
39/100- ECI—
- Price$0.66 / $1.00
- Context131K
- Our pick
UpstageSolar Pro 2
51/100- ECI—
- Price$0.25 / $0.25
- Context66K
Solar Pro 2 is our pick
Solar Pro 2 is the better all-round choice, scoring 51/100 against Qwen2.5-Coder-32B-Instruct (39) and Aya Expanse 32B (32). It leads on price and 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 priceSolar Pro 2Solar Pro 2 $0.25 · Qwen2.5-Coder-32B-Instruct $0.745 · Aya Expanse 32B $0.75 per 1M tokens (3:1 blend)
- Longest contextQwen2.5-Coder-32B-InstructQwen2.5-Coder-32B-Instruct 131,072 · Aya Expanse 32B 128,000 · Solar Pro 2 65,536 tokens
- Widest inputsSame inputsAya Expanse 32B: Text · Qwen2.5-Coder-32B-Instruct: Text · Solar Pro 2: Text
- Self-hostingAya Expanse 32B and Qwen2.5-Coder-32B-InstructPublishes downloadable weights (CC-BY-NC-4.0)
| Measure | Weight | Aya Expanse 32B | Qwen2.5-Coder-32B-Instruct | Solar Pro 2 |
|---|---|---|---|---|
| Price | 50% | 53 | 54 | 75 |
| Inputs & features | 30% | 0 | 25 | 35 |
| Context window | 20% | 24 | 25 | 12 |
| Overall | 100% | 32/100 | 39/100 | 51/100 |
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 | Aya Expanse 32BCohere | Qwen2.5-Coder-32B-InstructAlibaba (Qwen) | Solar Pro 2Upstage |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.50 | $0.66 | $0.25 (best) |
| Output | $1.50 | $1.00 | $0.25 (best) |
| Cached input | — | — | — |
| Blended (3:1) | $0.75 | $0.745 | $0.25 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Cohere API | Median of 7 providers | Official Upstage API |
| Limits | |||
| Context window | 128,000 tokens | 131,072 tokens (best) | 65,536 tokens |
| Max output | 4,000 tokens | 8,192 tokens (best) | 8,192 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | Yesminimal · high |
| Tool calling | No | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | OpenCC-BY-NC-4.0 | Open | Proprietary |
| API model ID | c4ai-aya-expanse-32b | — | solar-pro2 |
| API providers | 2 | 7 (best) | 2 |
| Released | Oct 24, 2024 | Nov 12, 2024 | May 20, 2025 |
| Knowledge cutoff | — | — | Mar 2025 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Aya Expanse 32B$8.00
- Qwen2.5-Coder-32B-Instruct$8.60
- Solar Pro 2$3.00
Which should you choose?
Which is better: Aya Expanse 32B, Qwen2.5-Coder-32B-Instruct or Solar Pro 2?
Solar Pro 2 is the better all-round choice, scoring 51/100 against Qwen2.5-Coder-32B-Instruct (39) and Aya Expanse 32B (32). It leads on price and 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, Aya Expanse 32B, Qwen2.5-Coder-32B-Instruct or Solar Pro 2?
Solar Pro 2 is cheaper at $0.25 input / $0.25 output per million tokens (official Upstage API price). Qwen2.5-Coder-32B-Instruct costs $0.66 input / $1.00 output per million tokens (median across 7 API providers); Aya Expanse 32B costs $0.50 input / $1.50 output per million tokens (official Cohere API price). At a typical mix of three input tokens to one output token, that is $0.25 per million tokens for Solar Pro 2 versus $0.745 for Qwen2.5-Coder-32B-Instruct (3× as much) and $0.75 for Aya Expanse 32B (3× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Aya Expanse 32B has not been scored yet, Qwen2.5-Coder-32B-Instruct has not been scored yet and Solar Pro 2 has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Aya Expanse 32B, Qwen2.5-Coder-32B-Instruct and Solar Pro 2 yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Aya Expanse 32B does not support tool calling, which most coding agents need.
Which has the bigger context window?
Qwen2.5-Coder-32B-Instruct has the largest context window at 131,072 tokens, against 128,000 for Aya Expanse 32B and 65,536 for Solar Pro 2. Maximum output per response: Aya Expanse 32B up to 4,000, Qwen2.5-Coder-32B-Instruct up to 8,192, Solar Pro 2 up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Aya Expanse 32B accepts text; Qwen2.5-Coder-32B-Instruct accepts text; Solar Pro 2 accepts text. They handle the same number of input types.
Are any of these open source?
Aya Expanse 32B and Qwen2.5-Coder-32B-Instruct publishes its weights (CC-BY-NC-4.0) and can be self-hosted; Solar Pro 2 is proprietary.
Which is newer?
Solar Pro 2 is the newest, released May 20, 2025. Qwen2.5-Coder-32B-Instruct came out Nov 12, 2024; Aya Expanse 32B came out Oct 24, 2024. Knowledge cutoff: Solar Pro 2 Mar 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.
