ZMIME
Comparison · 2 models · Updated Nov 2, 2026

Claude Haiku 3.5 vs Llama-3.2-1B

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. 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

  2. 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

  3. Add a model

    Make it a three-way comparison.

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 3.5Claude Haiku 3.5: Text, Images, PDFs · Llama-3.2-1B: Text
  • Self-hostingLlama-3.2-1BPublishes downloadable weights (Llama 3.2 Community License)
How the score is built
MeasureWeightClaude Haiku 3.5Llama-3.2-1B
CapabilityShared benchmarks50%2112
Price25%38100
Inputs & features15%600
Context window10%3225
Overall100%32/10034/100
02 — Side by side

Every spec in one table

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

Claude Haiku 3.5 vs Llama-3.2-1B specifications side by side
SpecificationClaude Haiku 3.5AnthropicLlama-3.2-1BMeta
Capability
Capabilities Index (ECI)127.0—
ECI rank#147 of 165—
GPQA DiamondGraduate-level science questions38.1% (best)23.9%
OTIS Mock AIME 2024–2025Competition mathematics4.3% (best)0.6%
Price per million tokens
Input$0.80$0.027 (best)
Output$4.00$0.201 (best)
Cached input——
Blended (3:1)$1.60$0.07 (best)
Long-context rateSame rateSame rate
Price sourceMedian of 3 providersMedian of 6 providers
Limits
Context window200,000 tokens (best)131,072 tokens
Max output8,192 tokens8,192 tokens
Inputs and features
TextYesYes
ImagesYesNo
PDFsYesNo
AudioNoNo
VideoNoNo
ReasoningNoNo
Tool callingYesNo
Structured outputNoNo
Availability
WeightsProprietaryOpenLlama 3.2 Community License
API model ID——
API providers46 (best)
ReleasedOct 22, 2024Sep 25, 2024
Knowledge cutoffJul 31, 2024Dec 2023
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.

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

Which should you choose?

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

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, Claude Haiku 3.5 or Llama-3.2-1B?

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 Claude Haiku 3.5 and Llama-3.2-1B 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: Claude Haiku 3.5 up to 8,192, Llama-3.2-1B up to 8,192 tokens.

Which can read images, PDFs, audio or video?

Claude Haiku 3.5 accepts text, images and PDFs; Llama-3.2-1B accepts text. 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: Claude Haiku 3.5 Jul 31, 2024, Llama-3.2-1B 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 Nov 2, 2026.

05 — Keep comparing

Related comparisons