Qwen2.5 32B Instruct vs Mistral Large 2.1 vs Llama-3.3-70B-Instruct
Too close to call on our weighted score (Llama-3.3-70B-Instruct 46, Qwen2.5 32B Instruct 43, Mistral Large 2.1 38). The right pick depends on what you value most.
Alibaba (Qwen)Qwen2.5 32B Instruct
43/100- ECI128.5
- Price$0.70 / $2.80
- Context131K
Mistral AIMistral Large 2.1
38/100- ECI128.5
- Price$2.00 / $6.00
- Context131K
MetaLlama-3.3-70B-Instruct
46/100- ECI127.3
- Price$0.59 / $0.724
- Context128K
Too close to call
It is close. Our weighted score puts them within 3 points (Llama-3.3-70B-Instruct 46/100, Qwen2.5 32B Instruct 43/100, Mistral Large 2.1 38/100), so choose by what matters most for your work: Qwen2.5 32B Instruct for raw capability and Llama-3.3-70B-Instruct on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityQwen2.5 32B Instruct and Mistral Large 2.1Capabilities Index (ECI): Qwen2.5 32B Instruct 128.5 · Mistral Large 2.1 128.5 · Llama-3.3-70B-Instruct 127.3
- Lowest priceLlama-3.3-70B-InstructLlama-3.3-70B-Instruct $0.624 · Qwen2.5 32B Instruct $1.23 · Mistral Large 2.1 $3.00 per 1M tokens (3:1 blend)
- Longest contextQwen2.5 32B Instruct and Mistral Large 2.1Qwen2.5 32B Instruct 131,072 · Mistral Large 2.1 131,072 · Llama-3.3-70B-Instruct 128,000 tokens
- Widest inputsSame inputsQwen2.5 32B Instruct: Text · Mistral Large 2.1: Text · Llama-3.3-70B-Instruct: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Qwen2.5 32B Instruct | Mistral Large 2.1 | Llama-3.3-70B-Instruct |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 51 | 51 | 49 |
| Price | 25% | 46 | 27 | 60 |
| Inputs & features | 15% | 25 | 25 | 25 |
| Context window | 10% | 24 | 24 | 24 |
| Overall | 100% | 43/100 | 38/100 | 46/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Qwen2.5 32B InstructAlibaba (Qwen) | Mistral Large 2.1Mistral AI | Llama-3.3-70B-InstructMeta |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 128.5 (best) | 128.5 (best) | 127.3 |
| ECI rank | #131 of 148 | #130 of 148 (best) | #133 of 148 |
| GPQA DiamondGraduate-level science questions | 46.1% | 51.3% (best) | 47.4% |
| OTIS Mock AIME 2024–2025Competition mathematics | 7.4% | 7.8% (best) | 5.1% |
| Price per million tokens | |||
| Input | $0.70 | $2.00 | $0.59 (best) |
| Output | $2.80 | $6.00 | $0.724 (best) |
| Cached input | — | — | — |
| Blended (3:1) | $1.23 | $3.00 | $0.624 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Alibaba API | Official Mistral API | Median of 21 providers |
| Limits | |||
| Context window | 131,072 tokens (best) | 131,072 tokens (best) | 128,000 tokens |
| Max output | 8,192 tokens | 16,384 tokens (best) | 4,096 tokens |
| 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 | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | Open | Open |
| API model ID | qwen2-5-32b-instruct | mistral-large-2411 | llama-3.3-70b-instruct |
| API providers | 1 | 2 | 24 (best) |
| Released | Sep 17, 2024 | Nov 18, 2024 | Dec 6, 2024 |
| Knowledge cutoff | Apr 2024 | Nov 2024 | Dec 2023 |
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 32B Instruct$12.60
- Mistral Large 2.1$32.00
- Llama-3.3-70B-Instruct$7.35
Which should you choose?
Which is better: Qwen2.5 32B Instruct, Mistral Large 2.1 or Llama-3.3-70B-Instruct?
It is close. Our weighted score puts them within 3 points (Llama-3.3-70B-Instruct 46/100, Qwen2.5 32B Instruct 43/100, Mistral Large 2.1 38/100), so choose by what matters most for your work: Qwen2.5 32B Instruct for raw capability and Llama-3.3-70B-Instruct on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Qwen2.5 32B Instruct, Mistral Large 2.1 or Llama-3.3-70B-Instruct?
Llama-3.3-70B-Instruct is cheaper at $0.59 input / $0.724 output per million tokens (median across 21 API providers; free on Llama). Qwen2.5 32B Instruct costs $0.70 input / $2.80 output per million tokens (official Alibaba API price); Mistral Large 2.1 costs $2.00 input / $6.00 output per million tokens (official Mistral API price). At a typical mix of three input tokens to one output token, that is $0.624 per million tokens for Llama-3.3-70B-Instruct versus $1.23 for Qwen2.5 32B Instruct (2× as much) and $3.00 for Mistral Large 2.1 (4.8× as much).
Which scores higher on benchmarks?
Qwen2.5 32B Instruct scores higher on the Capabilities Index (ECI): Qwen2.5 32B Instruct 128.5 (#131 of 148), Mistral Large 2.1 128.5 (#130 of 148) and Llama-3.3-70B-Instruct 127.3 (#133 of 148). The confidence ranges of the top two overlap (123.5–130.0 vs 123.8–130.8), so treat the gap as small. On individual benchmarks: GPQA Diamond — Mistral Large 2.1 51.3%, Llama-3.3-70B-Instruct 47.4%, Qwen2.5 32B Instruct 46.1%; OTIS Mock AIME 2024–2025 — Mistral Large 2.1 7.8%, Qwen2.5 32B Instruct 7.4%, Llama-3.3-70B-Instruct 5.1%.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen2.5 32B Instruct, Mistral Large 2.1 and Llama-3.3-70B-Instruct yet, so there is no like-for-like coding score. On overall capability, Qwen2.5 32B Instruct leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.
Which has the bigger context window?
Qwen2.5 32B Instruct and Mistral Large 2.1 have the largest context windows (131,072 and 131,072 tokens), against 128,000 for Llama-3.3-70B-Instruct. Maximum output per response: Qwen2.5 32B Instruct up to 8,192, Mistral Large 2.1 up to 16,384, Llama-3.3-70B-Instruct up to 4,096 tokens.
Which can read images, PDFs, audio or video?
Qwen2.5 32B Instruct accepts text; Mistral Large 2.1 accepts text; Llama-3.3-70B-Instruct accepts text. They handle the same number of input types.
Are any of these open source?
Yes, all three publish their weights, so you can self-host them.
Which is newer?
Llama-3.3-70B-Instruct is the newest, released Dec 6, 2024. Mistral Large 2.1 came out Nov 18, 2024; Qwen2.5 32B Instruct came out Sep 17, 2024. Knowledge cutoff: Qwen2.5 32B Instruct Apr 2024, Mistral Large 2.1 Nov 2024, Llama-3.3-70B-Instruct Dec 2023.
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.
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