Aya Expanse 32BvsQwen 2.5 32B
Complete comparison between Aya Expanse 32B (32B parameters, Cohere For AI) and Qwen 2.5 32B (32B, Alibaba). VRAM required by quantization, tokens per second measured on 4 reference GPUs, verdict by use case, license, installation commands. All figures are calculated from catalog data — no copy-pasting between pages.
In brief
| Feature | Aya Expanse 32B | Qwen 2.5 32B |
|---|---|---|
| Settings | 32B | 32B |
| Family | Aya | Qwen |
| Author | Cohere For AI | Alibaba |
| Origin | US | CN |
| License | CC-BY-NC 4.0 | Apache 2.0 |
| Context | 8,192 tokens | 131,072 tokens |
| Output | October 2024 | September 2024 |
Memory footprint
Approximate VRAM required for inference with an average context window. The winner (in green) is the model that uses less — smaller models have the edge.
| Quantization | Aya Expanse 32B | Qwen 2.5 32B |
|---|---|---|
| Q4_K_M (lightweight) | 19 GB | 19 GB |
| Q5_K_M (balanced) | 23 GB | 23 GB |
| Q8 (near-lossless) | 35 GB | 35 GB |
| FP16 (max quality) | 64 GB | 64 GB |
| CPU-only RAM | 32 GB | 32 GB |
Estimated speed (tokens/second)
Estimates based on the best quantization that can fit on each GPU. Actual figures depend on the prompt, context, and engine (llama.cpp, vLLM, MLX). Methodology.
| Reference GPU | Aya Expanse 32B | Qwen 2.5 32B |
|---|---|---|
| RTX 4090 (24 GB) | 30 tok/s · Q5_K_M | 30 tok/s · Q5_K_M |
| RTX 4080 (16 GB) | ✗ too heavy | ✗ too heavy |
| RTX 3060 12GB (12 GB) | ✗ too heavy | ✗ too heavy |
| Apple M4 Pro (48 GB) (36 GB) | 12 tok/s · Q8 | 12 tok/s · Q8 |
Verdict by use case
For each common use case, we indicate which of the two is better suited based on its tags, size, and specialization.
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Strengths and weaknesses
Aya Expanse 32B
23 languages, +25% on low-resource languages. 89.9% Dolly vs Mixtral 8x22B. ⚠ Non-commercial.
- +25% on low-resource
- 23 languages
- 89.9% Dolly vs Mixtral 8x22B
- ⚠ CC-BY-NC License
- 8k context only
Installation
Qwen 2.5 32B
Rivals 70B models on most benchmarks.
- Open-weight 32B reference model in 2024
- 128k context
- Apache 2.0
- Very strong at math, coding, and reasoning
- Requires 19 GB of VRAM in Q4
- Outperformed by Qwen 3 32B in 2025
Installation
Frequently asked questions
Which model runs best on RTX 4090 (24 GB): Aya Expanse 32B or Qwen 2.5 32B?
On an RTX 4090, Aya Expanse 32B runs in Q5_K_M (~30 tok/s), Qwen 2.5 32B in Q5_K_M (~30 tok/s). In pure throughput, Qwen 2.5 32B wins. See the configurator to test your exact GPU.
Which uses the least VRAM?
Both require the same VRAM in Q4 (19 GB). The choice then comes down to the license or perceived quality.
Can these models be used in commercial production?
Aya Expanse 32B is licensed under CC-BY-NC 4.0 — check the restrictions (especially the monthly user thresholds). Qwen 2.5 32B is under Apache 2.0 — also free to use. For SaaS, prefer Apache 2.0 or MIT.
Which one should you choose in 2026?
Depends on your primary constraint. Smaller / faster: Aya Expanse 32B (32B). More capable: Aya Expanse 32B (32B). If you're unsure, run the configurator with your GPU and use case — it will decide based on both.
Alternatives to consider
If neither works for you, here are some neighboring models you could explore.