Claude Haiku 3.5 vs Llama-3.2-1B vs Mistral Large 2.1
Too close to call on our weighted score (Llama-3.2-1B 34, Claude Haiku 3.5 32, Mistral Large 2.1 27). The right pick depends on what you value most.
AnthropicClaude Haiku 3.5
32/100- ECI127.0
- Price$0.80 / $4.00
- Context200K
MetaLlama-3.2-1B
34/100- ECI—
- Price$0.027 / $0.201
- Context131K
Mistral AIMistral Large 2.1
27/100- ECI128.6
- Price$2.00 / $6.00
- Context131K
Too close to call
It is close. Our weighted score puts them within 1 points (Llama-3.2-1B 34/100, Claude Haiku 3.5 32/100, Mistral Large 2.1 27/100), so choose by what matters most for your work: Mistral Large 2.1 for raw capability, Llama-3.2-1B on price and Claude Haiku 3.5 for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%. Capability uses the average of shared benchmarks (GPQA Diamond and OTIS Mock AIME 2024–2025), because Llama-3.2-1B has no Capabilities Index score yet.
- CapabilityMistral Large 2.1Shared benchmarks: Mistral Large 2.1 29.6% · Claude Haiku 3.5 21.2% · Llama-3.2-1B 12.2%
- Lowest priceLlama-3.2-1BLlama-3.2-1B $0.07 · Claude Haiku 3.5 $1.60 · Mistral Large 2.1 $3.00 per 1M tokens (3:1 blend)
- Longest contextClaude Haiku 3.5Claude Haiku 3.5 200,000 · Llama-3.2-1B 131,072 · Mistral Large 2.1 131,072 tokens
- Widest inputsClaude Haiku 3.5Claude Haiku 3.5: Text, Images, PDFs · Llama-3.2-1B: Text · Mistral Large 2.1: Text
- Self-hostingLlama-3.2-1B and Mistral Large 2.1Publishes downloadable weights (Llama 3.2 Community License)
| Measure | Weight | Claude Haiku 3.5 | Llama-3.2-1B | Mistral Large 2.1 |
|---|---|---|---|---|
| CapabilityShared benchmarks | 50% | 21 | 12 | 30 |
| Price | 25% | 38 | 100 | 26 |
| Inputs & features | 15% | 60 | 0 | 25 |
| Context window | 10% | 32 | 25 | 25 |
| Overall | 100% | 32/100 | 34/100 | 27/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Claude Haiku 3.5Anthropic | Llama-3.2-1BMeta | Mistral Large 2.1Mistral AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 127.0 | — | 128.6 (best) |
| ECI rank | #147 of 165 | — | #142 of 165 (best) |
| GPQA DiamondGraduate-level science questions | 38.1% | 23.9% | 51.3% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | 4.3% | 0.6% | 7.8% (best) |
| Price per million tokens | |||
| Input | $0.80 | $0.027 (best) | $2.00 |
| Output | $4.00 | $0.201 (best) | $6.00 |
| Cached input | — | — | — |
| Blended (3:1) | $1.60 | $0.07 (best) | $3.00 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 3 providers | Median of 6 providers | Median of 2 providers |
| Limits | |||
| Context window | 200,000 tokens (best) | 131,072 tokens | 131,072 tokens |
| Max output | 8,192 tokens | 8,192 tokens | 16,384 tokens (best) |
| 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 | No | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Proprietary | OpenLlama 3.2 Community License | Open |
| API model ID | — | — | — |
| API providers | 4 | 6 (best) | 2 |
| Released | Oct 22, 2024 | Sep 25, 2024 | Nov 18, 2024 |
| Knowledge cutoff | Jul 31, 2024 | Dec 2023 | Nov 2024 |
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$16.00
- Llama-3.2-1B$0.672
- Mistral Large 2.1$32.00
Which should you choose?
Which is better: Claude Haiku 3.5, Llama-3.2-1B or Mistral Large 2.1?
It is close. Our weighted score puts them within 1 points (Llama-3.2-1B 34/100, Claude Haiku 3.5 32/100, Mistral Large 2.1 27/100), so choose by what matters most for your work: Mistral Large 2.1 for raw capability, Llama-3.2-1B on price and Claude Haiku 3.5 for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%. Capability uses the average of shared benchmarks (GPQA Diamond and OTIS Mock AIME 2024–2025), because Llama-3.2-1B has no Capabilities Index score yet.
Which is cheaper, Claude Haiku 3.5, Llama-3.2-1B or Mistral Large 2.1?
Llama-3.2-1B is cheaper at $0.027 input / $0.201 output per million tokens (median across 6 API providers). Claude Haiku 3.5 costs $0.80 input / $4.00 output per million tokens (median across 3 API providers); Mistral Large 2.1 costs $2.00 input / $6.00 output per million tokens (median across 2 API providers). At a typical mix of three input tokens to one output token, that is $0.07 per million tokens for Llama-3.2-1B versus $1.60 for Claude Haiku 3.5 (23× as much) and $3.00 for Mistral Large 2.1 (43× as much).
Which scores higher on benchmarks?
Not every model here has a Capabilities Index score, so we compare the average of shared benchmarks (GPQA Diamond and OTIS Mock AIME 2024–2025): Mistral Large 2.1 29.6%, Claude Haiku 3.5 21.2% and Llama-3.2-1B 12.2%. On individual benchmarks: GPQA Diamond — Mistral Large 2.1 51.3%, Claude Haiku 3.5 38.1%, Llama-3.2-1B 23.9%; OTIS Mock AIME 2024–2025 — Mistral Large 2.1 7.8%, Claude Haiku 3.5 4.3%, Llama-3.2-1B 0.6%.
Which is better for coding?
There are no published SWE-bench Verified results for Claude Haiku 3.5, Llama-3.2-1B and Mistral Large 2.1 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. Note that Llama-3.2-1B does not support tool calling, which most coding agents need.
Which has the bigger context window?
Claude Haiku 3.5 has the largest context window at 200,000 tokens, against 131,072 for Llama-3.2-1B and 131,072 for Mistral Large 2.1. Maximum output per response: Claude Haiku 3.5 up to 8,192, Llama-3.2-1B up to 8,192, Mistral Large 2.1 up to 16,384 tokens.
Which can read images, PDFs, audio or video?
Claude Haiku 3.5 accepts text, images and PDFs; Llama-3.2-1B accepts text; Mistral Large 2.1 accepts text. Claude Haiku 3.5 handles the widest range of inputs.
Are any of these open source?
Llama-3.2-1B and Mistral Large 2.1 publishes its weights (Llama 3.2 Community License) and can be self-hosted; Claude Haiku 3.5 is proprietary.
Which is newer?
Mistral Large 2.1 is the newest, released Nov 18, 2024. Claude Haiku 3.5 came out Oct 22, 2024; Llama-3.2-1B came out Sep 25, 2024. Knowledge cutoff: Claude Haiku 3.5 Jul 31, 2024, Llama-3.2-1B Dec 2023, Mistral Large 2.1 Nov 2024.
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.
