Mistral Large 2407 vs Llama-3.1-70B-Instruct
Llama-3.1-70B-Instruct comes out ahead, 43 to 39 on our weighted score, and it is the cheaper option too.
Mistral AIMistral Large 2407
39/100- ECI127.6
- Price$2.00 / $6.00
- Context131K
- Our pick
MetaLlama-3.1-70B-Instruct
43/100- ECI125.9
- Price$0.72 / $0.72
- Context128K
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Make it a three-way comparison.
Llama-3.1-70B-Instruct is our pick
Llama-3.1-70B-Instruct is the better all-round choice, scoring 43/100 against Mistral Large 2407 (39). It leads on price. Mistral Large 2407 wins on capability and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityMistral Large 2407Capabilities Index (ECI): Mistral Large 2407 127.6 · Llama-3.1-70B-Instruct 125.9
- Lowest priceLlama-3.1-70B-InstructLlama-3.1-70B-Instruct $0.72 · Mistral Large 2407 $3.00 per 1M tokens (3:1 blend)
- Longest contextMistral Large 2407Mistral Large 2407 131,072 · Llama-3.1-70B-Instruct 128,000 tokens
- Widest inputsMistral Large 2407Mistral Large 2407: Text, PDFs · Llama-3.1-70B-Instruct: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Mistral Large 2407 | Llama-3.1-70B-Instruct |
|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 49 | 47 |
| Price | 25% | 26 | 54 |
| Inputs & features | 15% | 35 | 25 |
| Context window | 10% | 25 | 24 |
| Overall | 100% | 39/100 | 43/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Mistral Large 2407Mistral AI | Llama-3.1-70B-InstructMeta |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 127.6 (best) | 125.9 |
| ECI rank | #144 of 165 (best) | #149 of 165 |
| GPQA DiamondGraduate-level science questions | 49.0% (best) | 44.2% |
| OTIS Mock AIME 2024–2025Competition mathematics | 8.5% (best) | 3.6% |
| Price per million tokens | ||
| Input | $2.00 | $0.72 (best) |
| Output | $6.00 | $0.72 (best) |
| Cached input | — | — |
| Blended (3:1) | $3.00 | $0.72 (best) |
| Long-context rate | Same rate | Same rate |
| Price source | Median of 5 providers | Median of 8 providers |
| Limits | ||
| Context window | 131,072 tokens (best) | 128,000 tokens |
| Max output | 104,857 tokens (best) | 4,096 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | No |
| PDFs | Yes | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | No | No |
| Tool calling | Yes | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | Open | Open |
| API model ID | — | — |
| API providers | 5 | 8 (best) |
| Released | Jul 24, 2024 | Jul 23, 2024 |
| Knowledge cutoff | Mar 31, 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.
- Mistral Large 2407$32.00
- Llama-3.1-70B-Instruct$8.64
Which should you choose?
Which is better: Mistral Large 2407 or Llama-3.1-70B-Instruct?
Llama-3.1-70B-Instruct is the better all-round choice, scoring 43/100 against Mistral Large 2407 (39). It leads on price. Mistral Large 2407 wins on capability and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Mistral Large 2407 or Llama-3.1-70B-Instruct?
Llama-3.1-70B-Instruct is cheaper at $0.72 input / $0.72 output per million tokens (median across 8 API providers). Mistral Large 2407 costs $2.00 input / $6.00 output per million tokens (median across 5 API providers). At a typical mix of three input tokens to one output token, that is $0.72 per million tokens for Llama-3.1-70B-Instruct versus $3.00 for Mistral Large 2407 (4.2× as much).
Which scores higher on benchmarks?
Mistral Large 2407 scores higher on the Capabilities Index (ECI): Mistral Large 2407 127.6 (#144 of 165) and Llama-3.1-70B-Instruct 125.9 (#149 of 165). The confidence ranges of the top two overlap (123.3–129.4 vs 120.8–128.2), so treat the gap as small. On individual benchmarks: GPQA Diamond — Mistral Large 2407 49.0%, Llama-3.1-70B-Instruct 44.2%; OTIS Mock AIME 2024–2025 — Mistral Large 2407 8.5%, Llama-3.1-70B-Instruct 3.6%.
Which is better for coding?
There are no published SWE-bench Verified results for Mistral Large 2407 and Llama-3.1-70B-Instruct yet, so there is no like-for-like coding score. On overall capability, Mistral Large 2407 leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.
Which has the bigger context window?
Mistral Large 2407 has the largest context window at 131,072 tokens, against 128,000 for Llama-3.1-70B-Instruct. Maximum output per response: Mistral Large 2407 up to 104,857, Llama-3.1-70B-Instruct up to 4,096 tokens.
Which can read images, PDFs, audio or video?
Mistral Large 2407 accepts text and PDFs; Llama-3.1-70B-Instruct accepts text. Mistral Large 2407 handles the widest range of inputs.
Are any of these open source?
Yes, both publish their weights, so you can self-host them.
Which is newer?
Mistral Large 2407 is the newest, released Jul 24, 2024. Llama-3.1-70B-Instruct came out Jul 23, 2024. Knowledge cutoff: Mistral Large 2407 Mar 31, 2024, Llama-3.1-70B-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 Nov 2, 2026.
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