Aya Expanse 32B vs Nova Lite vs Qwen2.5-Coder-32B-Instruct
Nova Lite comes out ahead, 75 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
- Our pick
AmazonNova Lite
75/100- ECI—
- Price$0.06 / $0.24
- Context300K
Alibaba (Qwen)Qwen2.5-Coder-32B-Instruct
39/100- ECI—
- Price$0.66 / $1.00
- Context131K
Nova Lite is our pick
Nova Lite is the better all-round choice, scoring 75/100 against Qwen2.5-Coder-32B-Instruct (39) and Aya Expanse 32B (32). It leads on price, inputs & features and context window. 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 priceNova LiteNova Lite $0.105 · Qwen2.5-Coder-32B-Instruct $0.745 · Aya Expanse 32B $0.75 per 1M tokens (3:1 blend)
- Longest contextNova LiteNova Lite 300,000 · Qwen2.5-Coder-32B-Instruct 131,072 · Aya Expanse 32B 128,000 tokens
- Widest inputsNova LiteAya Expanse 32B: Text · Nova Lite: Text, Images, PDFs, Video · Qwen2.5-Coder-32B-Instruct: Text
- Self-hostingAya Expanse 32B and Qwen2.5-Coder-32B-InstructPublishes downloadable weights (CC-BY-NC-4.0)
| Measure | Weight | Aya Expanse 32B | Nova Lite | Qwen2.5-Coder-32B-Instruct |
|---|---|---|---|---|
| Price | 50% | 53 | 92 | 54 |
| Inputs & features | 30% | 0 | 70 | 25 |
| Context window | 20% | 24 | 39 | 25 |
| Overall | 100% | 32/100 | 75/100 | 39/100 |
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 | Nova LiteAmazon | Qwen2.5-Coder-32B-InstructAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.50 | $0.06 (best) | $0.66 |
| Output | $1.50 | $0.24 (best) | $1.00 |
| Cached input | — | $0.015 | — |
| Blended (3:1) | $0.75 | $0.105 (best) | $0.745 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Cohere API | Official Amazon Bedrock API | Median of 7 providers |
| Limits | |||
| Context window | 128,000 tokens | 300,000 tokens (best) | 131,072 tokens |
| Max output | 4,000 tokens | 10,000 tokens (best) | 8,192 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | No |
| PDFs | No | Yes | No |
| Audio | No | No | No |
| Video | No | Yes | No |
| Reasoning | No | No | No |
| Tool calling | No | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | OpenCC-BY-NC-4.0 | Proprietary | Open |
| API model ID | c4ai-aya-expanse-32b | amazon.nova-lite-v1:0 | — |
| API providers | 2 | 8 (best) | 7 |
| Released | Oct 24, 2024 | Dec 3, 2024 | Nov 12, 2024 |
| Knowledge cutoff | — | Oct 2024 | — |
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
- Nova Lite$1.08
- Qwen2.5-Coder-32B-Instruct$8.60
Which should you choose?
Which is better: Aya Expanse 32B, Nova Lite or Qwen2.5-Coder-32B-Instruct?
Nova Lite is the better all-round choice, scoring 75/100 against Qwen2.5-Coder-32B-Instruct (39) and Aya Expanse 32B (32). It leads on price, inputs & features and context window. 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, Nova Lite or Qwen2.5-Coder-32B-Instruct?
Nova Lite is cheaper at $0.06 input / $0.24 output per million tokens (official Amazon Bedrock 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 $0.105 per million tokens for Nova Lite versus $0.745 for Qwen2.5-Coder-32B-Instruct (7.1× as much) and $0.75 for Aya Expanse 32B (7.1× 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, Nova Lite has not been scored yet and Qwen2.5-Coder-32B-Instruct has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Aya Expanse 32B, Nova Lite and Qwen2.5-Coder-32B-Instruct 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?
Nova Lite has the largest context window at 300,000 tokens, against 131,072 for Qwen2.5-Coder-32B-Instruct and 128,000 for Aya Expanse 32B. Maximum output per response: Aya Expanse 32B up to 4,000, Nova Lite up to 10,000, Qwen2.5-Coder-32B-Instruct up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Aya Expanse 32B accepts text; Nova Lite accepts text, images, PDFs and video; Qwen2.5-Coder-32B-Instruct accepts text. Nova Lite handles the widest range of inputs.
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; Nova Lite is proprietary.
Which is newer?
Nova Lite is the newest, released Dec 3, 2024. Qwen2.5-Coder-32B-Instruct came out Nov 12, 2024; Aya Expanse 32B came out Oct 24, 2024. Knowledge cutoff: Nova Lite Oct 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.
