Mixtral 8x22B vs Llama-3.1-70B-Instruct
Llama-3.1-70B-Instruct comes out ahead, 44 to 33 on our weighted score, and it is the cheaper option too.
Mistral AIMixtral 8x22B
33/100- ECI122.0
- Price$2.00 / $6.00
- Context64K
- Our pick
MetaLlama-3.1-70B-Instruct
44/100- ECI125.9
- Price$0.72 / $0.72
- Context128K
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Llama-3.1-70B-Instruct is our pick
Llama-3.1-70B-Instruct is the better all-round choice, scoring 44/100 against Mixtral 8x22B (33). It leads on capability, price and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityLlama-3.1-70B-InstructCapabilities Index (ECI): Llama-3.1-70B-Instruct 125.9 · Mixtral 8x22B 122.0
- Lowest priceLlama-3.1-70B-InstructLlama-3.1-70B-Instruct $0.72 · Mixtral 8x22B $3.00 per 1M tokens (3:1 blend)
- Longest contextLlama-3.1-70B-InstructLlama-3.1-70B-Instruct 128,000 · Mixtral 8x22B 64,000 tokens
- Widest inputsSame inputsMixtral 8x22B: Text · Llama-3.1-70B-Instruct: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Mixtral 8x22B | Llama-3.1-70B-Instruct |
|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 43 | 48 |
| Price | 25% | 27 | 57 |
| Inputs & features | 15% | 25 | 25 |
| Context window | 10% | 12 | 24 |
| Overall | 100% | 33/100 | 44/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Mixtral 8x22BMistral AI | Llama-3.1-70B-InstructMeta |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 122.0 | 125.9 (best) |
| ECI rank | #139 of 148 | #136 of 148 (best) |
| GPQA DiamondGraduate-level science questions | 34.1% | 44.2% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 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 | Official Mistral API | Median of 5 providers |
| Limits | ||
| Context window | 64,000 tokens | 128,000 tokens (best) |
| Max output | 64,000 tokens (best) | 4,096 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | No |
| PDFs | No | 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 | open-mixtral-8x22b | — |
| API providers | 1 | 5 (best) |
| Released | Apr 17, 2024 | Jul 23, 2024 |
| Knowledge cutoff | Apr 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.
- Mixtral 8x22B$32.00
- Llama-3.1-70B-Instruct$8.64
Which should you choose?
Which is better: Mixtral 8x22B or Llama-3.1-70B-Instruct?
Llama-3.1-70B-Instruct is the better all-round choice, scoring 44/100 against Mixtral 8x22B (33). It leads on capability, price and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Mixtral 8x22B 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 5 API providers). Mixtral 8x22B 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 $0.72 per million tokens for Llama-3.1-70B-Instruct versus $3.00 for Mixtral 8x22B (4.2× as much).
Which scores higher on benchmarks?
Llama-3.1-70B-Instruct scores higher on the Capabilities Index (ECI): Llama-3.1-70B-Instruct 125.9 (#136 of 148) and Mixtral 8x22B 122.0 (#139 of 148). The confidence ranges of the top two overlap (121.0–128.1 vs 115.1–124.4), so treat the gap as small. On individual benchmarks: GPQA Diamond — Llama-3.1-70B-Instruct 44.2%, Mixtral 8x22B 34.1%.
Which is better for coding?
There are no published SWE-bench Verified results for Mixtral 8x22B and Llama-3.1-70B-Instruct yet, so there is no like-for-like coding score. On overall capability, Llama-3.1-70B-Instruct 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?
Llama-3.1-70B-Instruct has the largest context window at 128,000 tokens, against 64,000 for Mixtral 8x22B. Maximum output per response: Mixtral 8x22B up to 64,000, Llama-3.1-70B-Instruct up to 4,096 tokens.
Which can read images, PDFs, audio or video?
Mixtral 8x22B accepts text; Llama-3.1-70B-Instruct accepts text. They handle the same number of input types.
Are any of these open source?
Yes, both publish their weights, so you can self-host them.
Which is newer?
Llama-3.1-70B-Instruct is the newest, released Jul 23, 2024. Mixtral 8x22B came out Apr 17, 2024. Knowledge cutoff: Mixtral 8x22B Apr 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 Oct 4, 2026.
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