ZMIME
Comparison · 2 models · Updated Nov 2, 2026

Llama-3.2-1B vs Claude Haiku 3.5

Too close to call on our weighted score (Llama-3.2-1B 34, Claude Haiku 3.5 32). The right pick depends on what you value most.

  1. Meta

    Llama-3.2-1B

    Released Sep 25, 2024

    34/100
    • ECI—
    • Price$0.027 / $0.201
    • Context131K
    Full specs Remove Llama-3.2-1B

  2. Anthropic

    Claude Haiku 3.5

    Released Oct 22, 2024

    32/100
    • ECI127.0
    • Price$0.80 / $4.00
    • Context200K
    Full specs Remove Claude Haiku 3.5

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01 — Verdict

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), so choose by what matters most for your work: Claude Haiku 3.5 for raw capability and Llama-3.2-1B on price. 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.

  • CapabilityClaude Haiku 3.5Shared benchmarks: 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)
  • Longest contextClaude Haiku 3.5Claude Haiku 3.5 200,000 · Llama-3.2-1B 131,072 tokens
  • Widest inputsClaude Haiku 3.5Llama-3.2-1B: Text · Claude Haiku 3.5: Text, Images, PDFs
  • Self-hostingLlama-3.2-1BPublishes downloadable weights (Llama 3.2 Community License)
How the score is built
MeasureWeightLlama-3.2-1BClaude Haiku 3.5
CapabilityShared benchmarks50%1221
Price25%10038
Inputs & features15%060
Context window10%2532
Overall100%34/10032/100
02 — Side by side

Every spec in one table

Highlighted cells lead their row. Dashes mean the data is not published.

Llama-3.2-1B vs Claude Haiku 3.5 specifications side by side
SpecificationLlama-3.2-1BMetaClaude Haiku 3.5Anthropic
Capability
Capabilities Index (ECI)—127.0
ECI rank—#147 of 165
GPQA DiamondGraduate-level science questions23.9%38.1% (best)
OTIS Mock AIME 2024–2025Competition mathematics0.6%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 rateSame rateSame rate
Price sourceMedian of 6 providersMedian of 3 providers
Limits
Context window131,072 tokens200,000 tokens (best)
Max output8,192 tokens8,192 tokens
Inputs and features
TextYesYes
ImagesNoYes
PDFsNoYes
AudioNoNo
VideoNoNo
ReasoningNoNo
Tool callingNoYes
Structured outputNoNo
Availability
WeightsOpenLlama 3.2 Community LicenseProprietary
API model ID——
API providers6 (best)4
ReleasedSep 25, 2024Oct 22, 2024
Knowledge cutoffDec 2023Jul 31, 2024
03 — Cost

What would a month cost?

Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.

  • Llama-3.2-1B$0.672
  • Claude Haiku 3.5$16.00
04 — Questions

Which should you choose?

Which is better: Llama-3.2-1B or Claude Haiku 3.5?

It is close. Our weighted score puts them within 1 points (Llama-3.2-1B 34/100, Claude Haiku 3.5 32/100), so choose by what matters most for your work: Claude Haiku 3.5 for raw capability and Llama-3.2-1B on price. 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, 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).

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): Claude Haiku 3.5 21.2% and Llama-3.2-1B 12.2%. On individual benchmarks: GPQA Diamond — Claude Haiku 3.5 38.1%, Llama-3.2-1B 23.9%; OTIS Mock AIME 2024–2025 — Claude Haiku 3.5 4.3%, Llama-3.2-1B 0.6%.

Which is better for coding?

There are no published SWE-bench Verified results for Llama-3.2-1B 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. 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. Maximum output per response: 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-3.2-1B 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-3.2-1B 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-3.2-1B came out Sep 25, 2024. Knowledge cutoff: 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.

05 — Keep comparing

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