Claude Haiku 3.5 vs Mistral Large 2.1 vs Llama-3.3-70B-Instruct
Claude Haiku 3.5 comes out ahead, 49 to 42 and 41 on our weighted score.
- Our pick
AnthropicClaude Haiku 3.5
49/100- ECI127.2
- Price—
- Context200K
Mistral AIMistral Large 2.1
42/100- ECI128.5
- Price$2.00 / $6.00
- Context131K
MetaLlama-3.3-70B-Instruct
41/100- ECI127.3
- Price$0.59 / $0.724
- Context128K
Claude Haiku 3.5 is our pick
Claude Haiku 3.5 is the better all-round choice, scoring 49/100 against Mistral Large 2.1 (42) and Llama-3.3-70B-Instruct (41). It leads on inputs & features and context window. Mistral Large 2.1 wins on capability. The score weighs capability 67%, inputs & features 20%, context window 13%.
- CapabilityMistral Large 2.1Capabilities Index (ECI): Mistral Large 2.1 128.5 · Llama-3.3-70B-Instruct 127.3 · Claude Haiku 3.5 127.2
- Lowest priceLlama-3.3-70B-InstructLlama-3.3-70B-Instruct $0.624 · Mistral Large 2.1 $3.00 per 1M tokens (3:1 blend) · Claude Haiku 3.5 unpriced
- Longest contextClaude Haiku 3.5Claude Haiku 3.5 200,000 · Mistral Large 2.1 131,072 · Llama-3.3-70B-Instruct 128,000 tokens
- Widest inputsClaude Haiku 3.5Claude Haiku 3.5: Text, Images, PDFs · Mistral Large 2.1: Text · Llama-3.3-70B-Instruct: Text
- Self-hostingMistral Large 2.1 and Llama-3.3-70B-InstructPublishes downloadable weights
| Measure | Weight | Claude Haiku 3.5 | Mistral Large 2.1 | Llama-3.3-70B-Instruct |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 67% | 49 | 51 | 49 |
| Inputs & features | 20% | 60 | 25 | 25 |
| Context window | 13% | 32 | 24 | 24 |
| Overall | 100% | 49/100 | 42/100 | 41/100 |
Left out because at least one model lacks the data: price. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Claude Haiku 3.5Anthropic | Mistral Large 2.1Mistral AI | Llama-3.3-70B-InstructMeta |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 127.2 | 128.5 (best) | 127.3 |
| ECI rank | #134 of 148 | #130 of 148 (best) | #133 of 148 |
| GPQA DiamondGraduate-level science questions | 38.1% | 51.3% (best) | 47.4% |
| OTIS Mock AIME 2024–2025Competition mathematics | 4.3% | 7.8% (best) | 5.1% |
| Price per million tokens | |||
| Input | — | $2.00 | $0.59 (best) |
| Output | — | $6.00 | $0.724 (best) |
| Cached input | — | — | — |
| Blended (3:1) | — | $3.00 | $0.624 (best) |
| Long-context rate | — | Same rate | Same rate |
| Price source | — | Official Mistral API | Median of 21 providers |
| Limits | |||
| Context window | 200,000 tokens (best) | 131,072 tokens | 128,000 tokens |
| Max output | 8,192 tokens | 16,384 tokens (best) | 4,096 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | No |
| PDFs | Yes | 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 | Proprietary | Open | Open |
| API model ID | — | mistral-large-2411 | llama-3.3-70b-instruct |
| API providers | — | 2 | 24 (best) |
| Released | Oct 22, 2024 | Nov 18, 2024 | Dec 6, 2024 |
| Knowledge cutoff | Jul 31, 2024 | Nov 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.
- Claude Haiku 3.5—
- Mistral Large 2.1$32.00
- Llama-3.3-70B-Instruct$7.35
Which should you choose?
Which is better: Claude Haiku 3.5, Mistral Large 2.1 or Llama-3.3-70B-Instruct?
Claude Haiku 3.5 is the better all-round choice, scoring 49/100 against Mistral Large 2.1 (42) and Llama-3.3-70B-Instruct (41). It leads on inputs & features and context window. Mistral Large 2.1 wins on capability. The score weighs capability 67%, inputs & features 20%, context window 13%.
Which is cheaper, Claude Haiku 3.5, Mistral Large 2.1 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). 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 $0.624 per million tokens for Llama-3.3-70B-Instruct versus $3.00 for Mistral Large 2.1 (4.8× as much). Claude Haiku 3.5 has no published per-token price.
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), Llama-3.3-70B-Instruct 127.3 (#133 of 148) and Claude Haiku 3.5 127.2 (#134 of 148). The confidence ranges of the top two overlap (123.8–130.8 vs 122.5–129.5), so treat the gap as small. On individual benchmarks: GPQA Diamond — Mistral Large 2.1 51.3%, Llama-3.3-70B-Instruct 47.4%, Claude Haiku 3.5 38.1%; OTIS Mock AIME 2024–2025 — Mistral Large 2.1 7.8%, Llama-3.3-70B-Instruct 5.1%, Claude Haiku 3.5 4.3%.
Which is better for coding?
There are no published SWE-bench Verified results for Claude Haiku 3.5, Mistral Large 2.1 and Llama-3.3-70B-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?
Claude Haiku 3.5 has the largest context window at 200,000 tokens, against 131,072 for Mistral Large 2.1 and 128,000 for Llama-3.3-70B-Instruct. Maximum output per response: Claude Haiku 3.5 up to 8,192, Mistral Large 2.1 up to 16,384, Llama-3.3-70B-Instruct up to 4,096 tokens.
Which can read images, PDFs, audio or video?
Claude Haiku 3.5 accepts text, images and PDFs; Mistral Large 2.1 accepts text; Llama-3.3-70B-Instruct accepts text. Claude Haiku 3.5 handles the widest range of inputs.
Are any of these open source?
Mistral Large 2.1 and Llama-3.3-70B-Instruct publishes its weights and can be self-hosted; Claude Haiku 3.5 is proprietary.
Which is newer?
Llama-3.3-70B-Instruct is the newest, released Dec 6, 2024. Mistral Large 2.1 came out Nov 18, 2024; Claude Haiku 3.5 came out Oct 22, 2024. Knowledge cutoff: Claude Haiku 3.5 Jul 31, 2024, Mistral Large 2.1 Nov 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.
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