Llama-3.2-90B-Vision-Instruct vs Mistral Large vs Claude Haiku 3.5
Claude Haiku 3.5 comes out ahead, 48 to 44 and 40 on our weighted score, though Mistral Large is 2.1× cheaper per token.
MetaLlama-3.2-90B-Vision-Instruct
44/100- ECI125.5
- Price—
- Context128K
Mistral AIMistral Large
40/100- ECI122.0
- Price$0.50 / $1.50
- Context128K
- Our pick
AnthropicClaude Haiku 3.5
48/100- ECI127.0
- Price$0.80 / $4.00
- Context200K
Claude Haiku 3.5 is our pick
Claude Haiku 3.5 is the better all-round choice, scoring 48/100 against Llama-3.2-90B-Vision-Instruct (44) and Mistral Large (40). It leads on capability, inputs & features and context window. The score weighs capability 67%, inputs & features 20%, context window 13%.
- CapabilityClaude Haiku 3.5Capabilities Index (ECI): Claude Haiku 3.5 127.0 · Llama-3.2-90B-Vision-Instruct 125.5 · Mistral Large 122.0
- Lowest priceMistral LargeMistral Large $0.75 · Claude Haiku 3.5 $1.60 per 1M tokens (3:1 blend) · Llama-3.2-90B-Vision-Instruct unpriced
- Longest contextClaude Haiku 3.5Claude Haiku 3.5 200,000 · Llama-3.2-90B-Vision-Instruct 128,000 · Mistral Large 128,000 tokens
- Widest inputsClaude Haiku 3.5Llama-3.2-90B-Vision-Instruct: Text, Images · Mistral Large: Text, PDFs · Claude Haiku 3.5: Text, Images, PDFs
- Self-hostingLlama-3.2-90B-Vision-InstructPublishes downloadable weights (Llama 3.2 Community License)
| Measure | Weight | Llama-3.2-90B-Vision-Instruct | Mistral Large | Claude Haiku 3.5 |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 67% | 46 | 42 | 48 |
| Inputs & features | 20% | 50 | 45 | 60 |
| Context window | 13% | 24 | 24 | 32 |
| Overall | 100% | 44/100 | 40/100 | 48/100 |
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 | Llama-3.2-90B-Vision-InstructMeta | Mistral LargeMistral AI | Claude Haiku 3.5Anthropic |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 125.5 | 122.0 | 127.0 (best) |
| ECI rank | #150 of 165 | #153 of 165 | #147 of 165 (best) |
| GPQA DiamondGraduate-level science questions | 41.0% (best) | 38.8% | 38.1% |
| OTIS Mock AIME 2024–2025Competition mathematics | 2.6% | 1.9% | 4.3% (best) |
| Price per million tokens | |||
| Input | — | $0.50 (best) | $0.80 |
| Output | — | $1.50 (best) | $4.00 |
| Cached input | — | $0.05 | — |
| Blended (3:1) | — | $0.75 (best) | $1.60 |
| Long-context rate | — | Same rate | Same rate |
| Price source | — | Official Mistral API | Median of 3 providers |
| Limits | |||
| Context window | 128,000 tokens | 128,000 tokens | 200,000 tokens (best) |
| Max output | 4,096 tokens | 102,400 tokens (best) | 8,192 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | Yes |
| PDFs | No | Yes | Yes |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | OpenLlama 3.2 Community License | Proprietary | Proprietary |
| API model ID | — | mistral-large-latest | — |
| API providers | 1 | 11 (best) | 4 |
| Released | Sep 25, 2024 | Feb 26, 2024 | Oct 22, 2024 |
| Knowledge cutoff | Dec 2023 | Nov 30, 2024 | Jul 31, 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Llama-3.2-90B-Vision-Instruct—
- Mistral Large$8.00
- Claude Haiku 3.5$16.00
Which should you choose?
Which is better: Llama-3.2-90B-Vision-Instruct, Mistral Large or Claude Haiku 3.5?
Claude Haiku 3.5 is the better all-round choice, scoring 48/100 against Llama-3.2-90B-Vision-Instruct (44) and Mistral Large (40). It leads on capability, inputs & features and context window. The score weighs capability 67%, inputs & features 20%, context window 13%.
Which is cheaper, Llama-3.2-90B-Vision-Instruct, Mistral Large or Claude Haiku 3.5?
Mistral Large is cheaper at $0.50 input / $1.50 output per million tokens (official Mistral API price). Claude Haiku 3.5 costs $0.80 input / $4.00 output per million tokens (median across 3 API providers). At a typical mix of three input tokens to one output token, that is $0.75 per million tokens for Mistral Large versus $1.60 for Claude Haiku 3.5 (2.1× as much). Llama-3.2-90B-Vision-Instruct has no published per-token price.
Which scores higher on benchmarks?
Claude Haiku 3.5 scores higher on the Capabilities Index (ECI): Claude Haiku 3.5 127.0 (#147 of 165), Llama-3.2-90B-Vision-Instruct 125.5 (#150 of 165) and Mistral Large 122.0 (#153 of 165). The confidence ranges of the top two overlap (121.4–129.2 vs 120.3–127.4), so treat the gap as small. On individual benchmarks: GPQA Diamond — Llama-3.2-90B-Vision-Instruct 41.0%, Mistral Large 38.8%, Claude Haiku 3.5 38.1%; OTIS Mock AIME 2024–2025 — Claude Haiku 3.5 4.3%, Llama-3.2-90B-Vision-Instruct 2.6%, Mistral Large 1.9%.
Which is better for coding?
There are no published SWE-bench Verified results for Llama-3.2-90B-Vision-Instruct, Mistral Large and Claude Haiku 3.5 yet, so there is no like-for-like coding score. On overall capability, Claude Haiku 3.5 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 128,000 for Llama-3.2-90B-Vision-Instruct and 128,000 for Mistral Large. Maximum output per response: Llama-3.2-90B-Vision-Instruct up to 4,096, Mistral Large up to 102,400, Claude Haiku 3.5 up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Llama-3.2-90B-Vision-Instruct accepts text and images; Mistral Large accepts text and PDFs; Claude Haiku 3.5 accepts text, images and PDFs. Claude Haiku 3.5 handles the widest range of inputs.
Are any of these open source?
Llama-3.2-90B-Vision-Instruct publishes its weights (Llama 3.2 Community License) and can be self-hosted; Mistral Large and Claude Haiku 3.5 is proprietary.
Which is newer?
Claude Haiku 3.5 is the newest, released Oct 22, 2024. Llama-3.2-90B-Vision-Instruct came out Sep 25, 2024; Mistral Large came out Feb 26, 2024. Knowledge cutoff: Llama-3.2-90B-Vision-Instruct Dec 2023, Mistral Large Nov 30, 2024, Claude Haiku 3.5 Jul 31, 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.
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