Llama-3.2-90B-Vision-Instruct vs Llama-3.2-1B vs Claude Haiku 3.5
Too close to call on our weighted score (Claude Haiku 3.5 30, Llama-3.2-90B-Vision-Instruct 28, Llama-3.2-1B 11). The right pick depends on what you value most.
MetaLlama-3.2-90B-Vision-Instruct
28/100- ECI125.5
- Price—
- Context128K
- Meta
Llama-3.2-1B
11/100- ECI—
- Price$0.027 / $0.201
- Context131K
AnthropicClaude Haiku 3.5
30/100- ECI127.0
- Price$0.80 / $4.00
- Context200K
Too close to call
It is close. Our weighted score puts them within 3 points (Claude Haiku 3.5 30/100, Llama-3.2-90B-Vision-Instruct 28/100, Llama-3.2-1B 11/100), so choose by what matters most for your work: Llama-3.2-90B-Vision-Instruct for raw capability, Llama-3.2-1B on price and Claude Haiku 3.5 for long inputs. The score weighs capability 67%, inputs & features 20%, context window 13%. 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.
- CapabilityLlama-3.2-90B-Vision-InstructShared benchmarks: Llama-3.2-90B-Vision-Instruct 21.8% · 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 per 1M tokens (3:1 blend) · Llama-3.2-90B-Vision-Instruct unpriced
- Longest contextClaude Haiku 3.5Claude Haiku 3.5 200,000 · Llama-3.2-1B 131,072 · Llama-3.2-90B-Vision-Instruct 128,000 tokens
- Widest inputsClaude Haiku 3.5Llama-3.2-90B-Vision-Instruct: Text, Images · Llama-3.2-1B: Text · Claude Haiku 3.5: Text, Images, PDFs
- Self-hostingLlama-3.2-90B-Vision-Instruct and Llama-3.2-1BPublishes downloadable weights (Llama 3.2 Community License)
| Measure | Weight | Llama-3.2-90B-Vision-Instruct | Llama-3.2-1B | Claude Haiku 3.5 |
|---|---|---|---|---|
| CapabilityShared benchmarks | 67% | 22 | 12 | 21 |
| Inputs & features | 20% | 50 | 0 | 60 |
| Context window | 13% | 24 | 25 | 32 |
| Overall | 100% | 28/100 | 11/100 | 30/100 |
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 | Llama-3.2-1BMeta | Claude Haiku 3.5Anthropic |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 125.5 | — | 127.0 (best) |
| ECI rank | #150 of 165 | — | #147 of 165 (best) |
| GPQA DiamondGraduate-level science questions | 41.0% (best) | 23.9% | 38.1% |
| OTIS Mock AIME 2024–2025Competition mathematics | 2.6% | 0.6% | 4.3% (best) |
| Price per million tokens | |||
| Input | — | $0.027 (best) | $0.80 |
| Output | — | $0.201 (best) | $4.00 |
| Cached input | — | — | — |
| Blended (3:1) | — | $0.07 (best) | $1.60 |
| Long-context rate | — | Same rate | Same rate |
| Price source | — | Median of 6 providers | Median of 3 providers |
| Limits | |||
| Context window | 128,000 tokens | 131,072 tokens | 200,000 tokens (best) |
| Max output | 4,096 tokens | 8,192 tokens (best) | 8,192 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | Yes |
| PDFs | No | No | Yes |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | No |
| Tool calling | Yes | No | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | OpenLlama 3.2 Community License | OpenLlama 3.2 Community License | Proprietary |
| API model ID | — | — | — |
| API providers | 1 | 6 (best) | 4 |
| Released | Sep 25, 2024 | Sep 25, 2024 | Oct 22, 2024 |
| Knowledge cutoff | Dec 2023 | Dec 2023 | 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—
- Llama-3.2-1B$0.672
- Claude Haiku 3.5$16.00
Which should you choose?
Which is better: Llama-3.2-90B-Vision-Instruct, Llama-3.2-1B or Claude Haiku 3.5?
It is close. Our weighted score puts them within 3 points (Claude Haiku 3.5 30/100, Llama-3.2-90B-Vision-Instruct 28/100, Llama-3.2-1B 11/100), so choose by what matters most for your work: Llama-3.2-90B-Vision-Instruct for raw capability, Llama-3.2-1B on price and Claude Haiku 3.5 for long inputs. The score weighs capability 67%, inputs & features 20%, context window 13%. 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, Llama-3.2-90B-Vision-Instruct, Llama-3.2-1B or Claude Haiku 3.5?
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). 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). Llama-3.2-90B-Vision-Instruct has no published per-token price.
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): Llama-3.2-90B-Vision-Instruct 21.8%, Claude Haiku 3.5 21.2% and Llama-3.2-1B 12.2%. On individual benchmarks: GPQA Diamond — Llama-3.2-90B-Vision-Instruct 41.0%, Claude Haiku 3.5 38.1%, Llama-3.2-1B 23.9%; OTIS Mock AIME 2024–2025 — Claude Haiku 3.5 4.3%, Llama-3.2-90B-Vision-Instruct 2.6%, Llama-3.2-1B 0.6%.
Which is better for coding?
There are no published SWE-bench Verified results for Llama-3.2-90B-Vision-Instruct, Llama-3.2-1B and Claude Haiku 3.5 yet, so there is no like-for-like coding score. On overall capability, Llama-3.2-90B-Vision-Instruct 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 128,000 for Llama-3.2-90B-Vision-Instruct. Maximum output per response: Llama-3.2-90B-Vision-Instruct up to 4,096, Llama-3.2-1B up to 8,192, 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; Llama-3.2-1B accepts text; 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 and Llama-3.2-1B publishes its weights (Llama 3.2 Community License) and can be self-hosted; 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; Llama-3.2-1B came out Sep 25, 2024. Knowledge cutoff: Llama-3.2-90B-Vision-Instruct Dec 2023, Llama-3.2-1B Dec 2023, 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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