Mixtral 8x7B vs Llama-3.3-70B-Instruct vs Claude Haiku 3
Too close to call on our weighted score (Claude Haiku 3 47, Llama-3.3-70B-Instruct 46, Mixtral 8x7B 37). The right pick depends on what you value most.
Mistral AIMixtral 8x7B
37/100- ECI118.5
- Price$0.70 / $0.70
- Context32K
MetaLlama-3.3-70B-Instruct
46/100- ECI127.3
- Price$0.59 / $0.724
- Context128K
AnthropicClaude Haiku 3
47/100- ECI118.4
- Price$0.25 / $1.25
- Context200K
Too close to call
It is close. Our weighted score puts them within 2 points (Claude Haiku 3 47/100, Llama-3.3-70B-Instruct 46/100, Mixtral 8x7B 37/100), so choose by what matters most for your work: Llama-3.3-70B-Instruct for raw capability, Claude Haiku 3 on price and Claude Haiku 3 for long inputs. 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 · Claude Haiku 3 118.4
- Lowest priceClaude Haiku 3Claude Haiku 3 $0.50 · Llama-3.3-70B-Instruct $0.624 · Mixtral 8x7B $0.70 per 1M tokens (3:1 blend)
- Longest contextClaude Haiku 3Claude Haiku 3 200,000 · Llama-3.3-70B-Instruct 128,000 · Mixtral 8x7B 32,000 tokens
- Widest inputsClaude Haiku 3Mixtral 8x7B: Text · Llama-3.3-70B-Instruct: Text · Claude Haiku 3: Text, Images, PDFs
- Self-hostingMixtral 8x7B and Llama-3.3-70B-InstructPublishes downloadable weights
| Measure | Weight | Mixtral 8x7B | Llama-3.3-70B-Instruct | Claude Haiku 3 |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 38 | 49 | 38 |
| Price | 25% | 57 | 60 | 64 |
| Inputs & features | 15% | 25 | 25 | 60 |
| Context window | 10% | 0 | 24 | 32 |
| Overall | 100% | 37/100 | 46/100 | 47/100 |
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 | Claude Haiku 3Anthropic |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 118.5 | 127.3 (best) | 118.4 |
| ECI rank | #142 of 148 | #133 of 148 (best) | #143 of 148 |
| GPQA DiamondGraduate-level science questions | 30.6% | 47.4% (best) | 36.3% |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 5.1% (best) | 1.8% |
| Price per million tokens | |||
| Input | $0.70 | $0.59 | $0.25 (best) |
| Output | $0.70 (best) | $0.724 | $1.25 |
| Cached input | — | — | — |
| Blended (3:1) | $0.70 | $0.624 | $0.50 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Mistral API | Median of 21 providers | Median of 2 providers |
| Limits | |||
| Context window | 32,000 tokens | 128,000 tokens | 200,000 tokens (best) |
| Max output | 32,000 tokens (best) | 4,096 tokens | 4,096 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | Yes |
| PDFs | No | No | Yes |
| 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 | Proprietary |
| API model ID | open-mixtral-8x7b | llama-3.3-70b-instruct | — |
| API providers | 1 | 24 (best) | 2 |
| Released | Dec 11, 2023 | Dec 6, 2024 | Mar 13, 2024 |
| Knowledge cutoff | Jan 2024 | Dec 2023 | Aug 31, 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
- Claude Haiku 3$5.00
Which should you choose?
Which is better: Mixtral 8x7B, Llama-3.3-70B-Instruct or Claude Haiku 3?
It is close. Our weighted score puts them within 2 points (Claude Haiku 3 47/100, Llama-3.3-70B-Instruct 46/100, Mixtral 8x7B 37/100), so choose by what matters most for your work: Llama-3.3-70B-Instruct for raw capability, Claude Haiku 3 on price and Claude Haiku 3 for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Mixtral 8x7B, Llama-3.3-70B-Instruct or Claude Haiku 3?
Claude Haiku 3 is cheaper at $0.25 input / $1.25 output per million tokens (median across 2 API providers). Llama-3.3-70B-Instruct costs $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 $0.50 per million tokens for Claude Haiku 3 versus $0.624 for Llama-3.3-70B-Instruct (1.2× as much) and $0.70 for Mixtral 8x7B (1.4× 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), Mixtral 8x7B 118.5 (#142 of 148) and Claude Haiku 3 118.4 (#143 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%, Claude Haiku 3 36.3%, Mixtral 8x7B 30.6%.
Which is better for coding?
There are no published SWE-bench Verified results for Mixtral 8x7B, Llama-3.3-70B-Instruct and Claude Haiku 3 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. All three support tool calling for agent workflows.
Which has the bigger context window?
Claude Haiku 3 has the largest context window at 200,000 tokens, against 128,000 for Llama-3.3-70B-Instruct and 32,000 for Mixtral 8x7B. Maximum output per response: Mixtral 8x7B up to 32,000, Llama-3.3-70B-Instruct up to 4,096, Claude Haiku 3 up to 4,096 tokens.
Which can read images, PDFs, audio or video?
Mixtral 8x7B accepts text; Llama-3.3-70B-Instruct accepts text; Claude Haiku 3 accepts text, images and PDFs. Claude Haiku 3 handles the widest range of inputs.
Are any of these open source?
Mixtral 8x7B and Llama-3.3-70B-Instruct publishes its weights and can be self-hosted; Claude Haiku 3 is proprietary.
Which is newer?
Llama-3.3-70B-Instruct is the newest, released Dec 6, 2024. Claude Haiku 3 came out Mar 13, 2024; Mixtral 8x7B came out Dec 11, 2023. Knowledge cutoff: Mixtral 8x7B Jan 2024, Llama-3.3-70B-Instruct Dec 2023, Claude Haiku 3 Aug 31, 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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