Llama-3.1-8B-Instruct vs Mistral Large 2.1 vs Qwen2.5 32B Instruct
Llama-3.1-8B-Instruct comes out ahead, 46 to 43 and 38 on our weighted score, and it is the cheaper option too.
- Our pick
MetaLlama-3.1-8B-Instruct
46/100- ECI116.6
- Price$0.152 / $0.167
- Context128K
Mistral AIMistral Large 2.1
38/100- ECI128.5
- Price$2.00 / $6.00
- Context131K
Alibaba (Qwen)Qwen2.5 32B Instruct
43/100- ECI128.5
- Price$0.70 / $2.80
- Context131K
Llama-3.1-8B-Instruct is our pick
Llama-3.1-8B-Instruct is the better all-round choice, scoring 46/100 against Qwen2.5 32B Instruct (43) and Mistral Large 2.1 (38). It leads on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityMistral Large 2.1 and Qwen2.5 32B InstructCapabilities Index (ECI): Mistral Large 2.1 128.5 · Qwen2.5 32B Instruct 128.5 · Llama-3.1-8B-Instruct 116.6
- Lowest priceLlama-3.1-8B-InstructLlama-3.1-8B-Instruct $0.156 · Qwen2.5 32B Instruct $1.23 · Mistral Large 2.1 $3.00 per 1M tokens (3:1 blend)
- Longest contextMistral Large 2.1 and Qwen2.5 32B InstructMistral Large 2.1 131,072 · Qwen2.5 32B Instruct 131,072 · Llama-3.1-8B-Instruct 128,000 tokens
- Widest inputsSame inputsLlama-3.1-8B-Instruct: Text · Mistral Large 2.1: Text · Qwen2.5 32B Instruct: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Llama-3.1-8B-Instruct | Mistral Large 2.1 | Qwen2.5 32B Instruct |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 36 | 51 | 51 |
| Price | 25% | 88 | 27 | 46 |
| Inputs & features | 15% | 25 | 25 | 25 |
| Context window | 10% | 24 | 24 | 24 |
| Overall | 100% | 46/100 | 38/100 | 43/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Llama-3.1-8B-InstructMeta | Mistral Large 2.1Mistral AI | Qwen2.5 32B InstructAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 116.6 | 128.5 (best) | 128.5 (best) |
| ECI rank | #145 of 148 | #130 of 148 (best) | #131 of 148 |
| GPQA DiamondGraduate-level science questions | 27.0% | 51.3% (best) | 46.1% |
| OTIS Mock AIME 2024–2025Competition mathematics | 1.7% | 7.8% (best) | 7.4% |
| Price per million tokens | |||
| Input | $0.152 (best) | $2.00 | $0.70 |
| Output | $0.167 (best) | $6.00 | $2.80 |
| Cached input | — | — | — |
| Blended (3:1) | $0.156 (best) | $3.00 | $1.23 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 9 providers | Official Mistral API | Official Alibaba API |
| Limits | |||
| Context window | 128,000 tokens | 131,072 tokens (best) | 131,072 tokens (best) |
| Max output | 4,096 tokens | 16,384 tokens (best) | 8,192 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 | — | mistral-large-2411 | qwen2-5-32b-instruct |
| API providers | 9 (best) | 2 | 1 |
| Released | Jul 23, 2024 | Nov 18, 2024 | Sep 17, 2024 |
| Knowledge cutoff | Dec 2023 | Nov 2024 | Apr 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Llama-3.1-8B-Instruct$1.85
- Mistral Large 2.1$32.00
- Qwen2.5 32B Instruct$12.60
Which should you choose?
Which is better: Llama-3.1-8B-Instruct, Mistral Large 2.1 or Qwen2.5 32B Instruct?
Llama-3.1-8B-Instruct is the better all-round choice, scoring 46/100 against Qwen2.5 32B Instruct (43) and Mistral Large 2.1 (38). It leads on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Llama-3.1-8B-Instruct, Mistral Large 2.1 or Qwen2.5 32B Instruct?
Llama-3.1-8B-Instruct is cheaper at $0.152 input / $0.167 output per million tokens (median across 9 API providers). 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 $0.156 per million tokens for Llama-3.1-8B-Instruct versus $1.23 for Qwen2.5 32B Instruct (7.9× as much) and $3.00 for Mistral Large 2.1 (19× as much).
Which scores higher on benchmarks?
Mistral Large 2.1 scores higher on the Capabilities Index (ECI): Mistral Large 2.1 128.5 (#130 of 148), Qwen2.5 32B Instruct 128.5 (#131 of 148) and Llama-3.1-8B-Instruct 116.6 (#145 of 148). The confidence ranges of the top two overlap (123.8–130.8 vs 123.5–130.0), so treat the gap as small. On individual benchmarks: GPQA Diamond — Mistral Large 2.1 51.3%, Qwen2.5 32B Instruct 46.1%, Llama-3.1-8B-Instruct 27.0%; OTIS Mock AIME 2024–2025 — Mistral Large 2.1 7.8%, Qwen2.5 32B Instruct 7.4%, Llama-3.1-8B-Instruct 1.7%.
Which is better for coding?
There are no published SWE-bench Verified results for Llama-3.1-8B-Instruct, Mistral Large 2.1 and Qwen2.5 32B Instruct yet, so there is no like-for-like coding score. On overall capability, Mistral Large 2.1 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?
Mistral Large 2.1 and Qwen2.5 32B Instruct have the largest context windows (131,072 and 131,072 tokens), against 128,000 for Llama-3.1-8B-Instruct. Maximum output per response: Llama-3.1-8B-Instruct up to 4,096, Mistral Large 2.1 up to 16,384, Qwen2.5 32B Instruct up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Llama-3.1-8B-Instruct accepts text; Mistral Large 2.1 accepts text; Qwen2.5 32B 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?
Mistral Large 2.1 is the newest, released Nov 18, 2024. Qwen2.5 32B Instruct came out Sep 17, 2024; Llama-3.1-8B-Instruct came out Jul 23, 2024. Knowledge cutoff: Llama-3.1-8B-Instruct Dec 2023, Mistral Large 2.1 Nov 2024, Qwen2.5 32B Instruct Apr 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 Oct 4, 2026.
Related comparisons
- Llama-3.1-8B-Instruct vs Ministral 8B InstructMistral AI
- Llama-3.1-8B-Instruct vs Qwen2.5 7B InstructAlibaba (Qwen) · ECI 118.5
- Llama-3.1-8B-Instruct vs Gemma 3 4B ITGoogle · ECI 116.1
- Llama-3.1-8B-Instruct vs Claude Haiku 3Anthropic · ECI 118.4
- Mistral Large 2.1 vs Qwen2.5 72B InstructAlibaba (Qwen) · ECI 129.0
- Mistral Large 2.1 vs GPT-4oOpenAI · ECI 129.0
