ZMIME
Comparison · 3 models · Updated Nov 2, 2026

Gemma 3 4B IT vs Claude Haiku 3.5 vs Llama-3.2-1B

Gemma 3 4B IT comes out ahead, 43 to 34 and 32 on our weighted score, and it is the cheaper option too.

  1. Our pick

    Google

    Gemma 3 4B IT

    Released Mar 12, 2025

    43/100
    • ECI115.8
    • Price$0.05 / $0.10
    • Context131K
  2. Anthropic

    Claude Haiku 3.5

    Released Oct 22, 2024

    32/100
    • ECI127.0
    • Price$0.80 / $4.00
    • Context200K
  3. Meta

    Llama-3.2-1B

    Released Sep 25, 2024

    34/100
    • ECI—
    • Price$0.027 / $0.201
    • Context131K
01 — Verdict

Gemma 3 4B IT is our pick

Gemma 3 4B IT is the better all-round choice, scoring 43/100 against Llama-3.2-1B (34) and Claude Haiku 3.5 (32). Claude Haiku 3.5 wins on capability, inputs & features and context window. 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% · Gemma 3 4B IT 15.4% · Llama-3.2-1B 12.2%
  • Lowest priceGemma 3 4B ITGemma 3 4B IT $0.063 · Llama-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 · Gemma 3 4B IT 131,072 · Llama-3.2-1B 131,072 tokens
  • Widest inputsClaude Haiku 3.5Gemma 3 4B IT: Text, Images · Claude Haiku 3.5: Text, Images, PDFs · Llama-3.2-1B: Text
  • Self-hostingGemma 3 4B IT and Llama-3.2-1BPublishes downloadable weights (Llama 3.2 Community License)
How the score is built
MeasureWeightGemma 3 4B ITClaude Haiku 3.5Llama-3.2-1B
CapabilityShared benchmarks50%152112
Price25%10038100
Inputs & features15%50600
Context window10%253225
Overall100%43/10032/10034/100
02 — Side by side

Every spec in one table

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

Gemma 3 4B IT vs Claude Haiku 3.5 vs Llama-3.2-1B specifications side by side
SpecificationGemma 3 4B ITGoogleClaude Haiku 3.5AnthropicLlama-3.2-1BMeta
Capability
Capabilities Index (ECI)115.8127.0 (best)—
ECI rank#163 of 165#147 of 165 (best)—
GPQA DiamondGraduate-level science questions23.2%38.1% (best)23.9%
OTIS Mock AIME 2024–2025Competition mathematics7.5% (best)4.3%0.6%
Price per million tokens
Input$0.05$0.80$0.027 (best)
Output$0.10 (best)$4.00$0.201
Cached input———
Blended (3:1)$0.063 (best)$1.60$0.07
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 9 providersMedian of 3 providersMedian of 6 providers
Limits
Context window131,072 tokens200,000 tokens (best)131,072 tokens
Max output131,072 tokens (best)8,192 tokens8,192 tokens
Inputs and features
TextYesYesYes
ImagesYesYesNo
PDFsNoYesNo
AudioNoNoNo
VideoNoNoNo
ReasoningNoNoNo
Tool callingYesYesNo
Structured outputNoNoNo
Availability
WeightsOpenProprietaryOpenLlama 3.2 Community License
API model ID———
API providers10 (best)46
ReleasedMar 12, 2025Oct 22, 2024Sep 25, 2024
Knowledge cutoffAug 2024Jul 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.

  • Gemma 3 4B IT$0.70
  • Claude Haiku 3.5$16.00
  • Llama-3.2-1B$0.672
04 — Questions

Which should you choose?

Which is better: Gemma 3 4B IT, Claude Haiku 3.5 or Llama-3.2-1B?

Gemma 3 4B IT is the better all-round choice, scoring 43/100 against Llama-3.2-1B (34) and Claude Haiku 3.5 (32). Claude Haiku 3.5 wins on capability, inputs & features and context window. 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, Gemma 3 4B IT, Claude Haiku 3.5 or Llama-3.2-1B?

Gemma 3 4B IT is cheaper at $0.05 input / $0.10 output per million tokens (median across 9 API providers). Llama-3.2-1B costs $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 $0.063 per million tokens for Gemma 3 4B IT versus $0.07 for Llama-3.2-1B (1.1× as much) and $1.60 for Claude Haiku 3.5 (26× 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%, Gemma 3 4B IT 15.4% and Llama-3.2-1B 12.2%. On individual benchmarks: GPQA Diamond — Claude Haiku 3.5 38.1%, Llama-3.2-1B 23.9%, Gemma 3 4B IT 23.2%; OTIS Mock AIME 2024–2025 — Gemma 3 4B IT 7.5%, 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 Gemma 3 4B IT, 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 Gemma 3 4B IT and 131,072 for Llama-3.2-1B. Maximum output per response: Gemma 3 4B IT up to 131,072, 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?

Gemma 3 4B IT accepts text and images; 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?

Gemma 3 4B IT 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?

Gemma 3 4B IT is the newest, released Mar 12, 2025. Claude Haiku 3.5 came out Oct 22, 2024; Llama-3.2-1B came out Sep 25, 2024. Knowledge cutoff: Gemma 3 4B IT Aug 2024, 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.