Mixtral 8x7B vs Llama-3.3-70B-Instruct
Llama-3.3-70B-Instruct comes out ahead, 46 to 37 on our weighted score, and it is the cheaper option too.
Mistral AIMixtral 8x7B
37/100- ECI118.5
- Price$0.70 / $0.70
- Context32K
- Our pick
MetaLlama-3.3-70B-Instruct
46/100- ECI127.3
- Price$0.59 / $0.724
- Context128K
Add a model
Make it a three-way comparison.
Llama-3.3-70B-Instruct is our pick
Llama-3.3-70B-Instruct is the better all-round choice, scoring 46/100 against Mixtral 8x7B (37). It leads on capability, price and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityLlama-3.3-70B-InstructCapabilities Index (ECI): Llama-3.3-70B-Instruct 127.3 · Mixtral 8x7B 118.5
- Lowest priceLlama-3.3-70B-InstructLlama-3.3-70B-Instruct $0.624 · Mixtral 8x7B $0.70 per 1M tokens (3:1 blend)
- Longest contextLlama-3.3-70B-InstructLlama-3.3-70B-Instruct 128,000 · Mixtral 8x7B 32,000 tokens
- Widest inputsSame inputsMixtral 8x7B: Text · Llama-3.3-70B-Instruct: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Mixtral 8x7B | Llama-3.3-70B-Instruct |
|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 38 | 49 |
| Price | 25% | 57 | 60 |
| Inputs & features | 15% | 25 | 25 |
| Context window | 10% | 0 | 24 |
| Overall | 100% | 37/100 | 46/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Mixtral 8x7BMistral AI | Llama-3.3-70B-InstructMeta |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 118.5 | 127.3 (best) |
| ECI rank | #142 of 148 | #133 of 148 (best) |
| GPQA DiamondGraduate-level science questions | 30.6% | 47.4% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 5.1% |
| Price per million tokens | ||
| Input | $0.70 | $0.59 (best) |
| Output | $0.70 (best) | $0.724 |
| Cached input | — | — |
| Blended (3:1) | $0.70 | $0.624 (best) |
| Long-context rate | Same rate | Same rate |
| Price source | Official Mistral API | Median of 21 providers |
| Limits | ||
| Context window | 32,000 tokens | 128,000 tokens (best) |
| Max output | 32,000 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-8x7b | llama-3.3-70b-instruct |
| API providers | 1 | 24 (best) |
| Released | Dec 11, 2023 | Dec 6, 2024 |
| Knowledge cutoff | Jan 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 8x7B$8.40
- Llama-3.3-70B-Instruct$7.35
Which should you choose?
Which is better: Mixtral 8x7B or Llama-3.3-70B-Instruct?
Llama-3.3-70B-Instruct is the better all-round choice, scoring 46/100 against Mixtral 8x7B (37). 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 8x7B 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). Mixtral 8x7B costs $0.70 input / $0.70 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 $0.70 for Mixtral 8x7B (1.1× as much).
Which scores higher on benchmarks?
Llama-3.3-70B-Instruct scores higher on the Capabilities Index (ECI): Llama-3.3-70B-Instruct 127.3 (#133 of 148) and Mixtral 8x7B 118.5 (#142 of 148). Their confidence ranges do not overlap (122.5–129.5 vs 111.3–121.3), so the gap is a real one. On individual benchmarks: GPQA Diamond — Llama-3.3-70B-Instruct 47.4%, Mixtral 8x7B 30.6%.
Which is better for coding?
There are no published SWE-bench Verified results for Mixtral 8x7B and Llama-3.3-70B-Instruct yet, so there is no like-for-like coding score. On overall capability, Llama-3.3-70B-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-3.3-70B-Instruct has the largest context window at 128,000 tokens, against 32,000 for Mixtral 8x7B. Maximum output per response: Mixtral 8x7B up to 32,000, Llama-3.3-70B-Instruct up to 4,096 tokens.
Which can read images, PDFs, audio or video?
Mixtral 8x7B accepts text; Llama-3.3-70B-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-3.3-70B-Instruct is the newest, released Dec 6, 2024. Mixtral 8x7B came out Dec 11, 2023. Knowledge cutoff: Mixtral 8x7B Jan 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.
Related comparisons
- Add Claude Haiku 3Three-way comparison
- Mixtral 8x7B vs Claude Haiku 3Anthropic · ECI 118.4
- Mixtral 8x7B vs Qwen2.5 7B InstructAlibaba (Qwen) · ECI 118.5
- Mixtral 8x7B vs Llama-3.1-70B-InstructMeta · ECI 125.9
- Mixtral 8x7B vs Nova ProAmazon · ECI 123.8
- Llama-3.3-70B-Instruct vs Mistral Small 3.1 24BMistral AI · ECI 127.5
- Llama-3.3-70B-Instruct vs Qwen2.5 32B InstructAlibaba (Qwen) · ECI 128.5
