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Comparison · 2 models · Updated Oct 4, 2026

Llama-3.3-70B-Instruct vs Claude Haiku 4.5

Claude Haiku 4.5 comes out ahead, 58 to 46 on our weighted score, though Llama-3.3-70B-Instruct is 3.2× cheaper per token.

  1. Meta

    Llama-3.3-70B-Instruct

    Released Dec 6, 2024

    46/100
    • ECI127.3
    • Price$0.59 / $0.724
    • Context128K
    Full specs Remove Llama-3.3-70B-Instruct
  2. Our pick

    Anthropic

    Claude Haiku 4.5

    Released Oct 15, 2025

    58/100
    • ECI142.4
    • Price$1.00 / $5.00
    • Context200K
    Full specs Remove Claude Haiku 4.5

  3. Add a model

    Make it a three-way comparison.

01 — Verdict

Claude Haiku 4.5 is our pick

Claude Haiku 4.5 is the better all-round choice, scoring 58/100 against Llama-3.3-70B-Instruct (46). It leads on capability, inputs & features and context window. Llama-3.3-70B-Instruct wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityClaude Haiku 4.5Capabilities Index (ECI): Claude Haiku 4.5 142.4 · Llama-3.3-70B-Instruct 127.3
  • Lowest priceLlama-3.3-70B-InstructLlama-3.3-70B-Instruct $0.624 · Claude Haiku 4.5 $2.00 per 1M tokens (3:1 blend)
  • Longest contextClaude Haiku 4.5Claude Haiku 4.5 200,000 · Llama-3.3-70B-Instruct 128,000 tokens
  • Widest inputsClaude Haiku 4.5Llama-3.3-70B-Instruct: Text · Claude Haiku 4.5: Text, Images, PDFs
  • Self-hostingLlama-3.3-70B-InstructPublishes downloadable weights
How the score is built
MeasureWeightLlama-3.3-70B-InstructClaude Haiku 4.5
CapabilityCapabilities Index (ECI)50%4969
Price25%6036
Inputs & features15%2580
Context window10%2432
Overall100%46/10058/100
02 — Side by side

Every spec in one table

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

Llama-3.3-70B-Instruct vs Claude Haiku 4.5 specifications side by side
SpecificationLlama-3.3-70B-InstructMetaClaude Haiku 4.5Anthropic
Capability
Capabilities Index (ECI)127.3142.4 (best)
ECI rank#133 of 148#90 of 148 (best)
GPQA DiamondGraduate-level science questions47.4%71.2% (best)
OTIS Mock AIME 2024–2025Competition mathematics5.1%66.7% (best)
SimpleQA VerifiedShort factual questions—13.2%
Price per million tokens
Input$0.59 (best)$1.00
Output$0.724 (best)$5.00
Cached input—$0.10
Blended (3:1)$0.624 (best)$2.00
Long-context rateSame rateSame rate
Price sourceMedian of 21 providersOfficial Anthropic API
Limits
Context window128,000 tokens200,000 tokens (best)
Max output4,096 tokens64,000 tokens (best)
Inputs and features
TextYesYes
ImagesNoYes
PDFsNoYes
AudioNoNo
VideoNoNo
ReasoningNoYes
Tool callingYesYes
Structured outputNoYes
Availability
WeightsOpenProprietary
API model IDllama-3.3-70b-instructclaude-haiku-4-5
API providers2434 (best)
ReleasedDec 6, 2024Oct 15, 2025
Knowledge cutoffDec 2023Feb 28, 2025
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-3.3-70B-Instruct$7.35
  • Claude Haiku 4.5$20.00
04 — Questions

Which should you choose?

Which is better: Llama-3.3-70B-Instruct or Claude Haiku 4.5?

Claude Haiku 4.5 is the better all-round choice, scoring 58/100 against Llama-3.3-70B-Instruct (46). It leads on capability, inputs & features and context window. Llama-3.3-70B-Instruct wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Llama-3.3-70B-Instruct or Claude Haiku 4.5?

Llama-3.3-70B-Instruct is cheaper at $0.59 input / $0.724 output per million tokens (median across 21 API providers; free on Llama). Claude Haiku 4.5 costs $1.00 input / $5.00 output per million tokens (official Anthropic API price). At a typical mix of three input tokens to one output token, that is $0.624 per million tokens for Llama-3.3-70B-Instruct versus $2.00 for Claude Haiku 4.5 (3.2× as much).

Which scores higher on benchmarks?

Claude Haiku 4.5 scores higher on the Capabilities Index (ECI): Claude Haiku 4.5 142.4 (#90 of 148) and Llama-3.3-70B-Instruct 127.3 (#133 of 148). Their confidence ranges do not overlap (139.5–144.3 vs 122.5–129.5), so the gap is a real one. On individual benchmarks: GPQA Diamond — Claude Haiku 4.5 71.2%, Llama-3.3-70B-Instruct 47.4%; OTIS Mock AIME 2024–2025 — Claude Haiku 4.5 66.7%, Llama-3.3-70B-Instruct 5.1%.

Which is better for coding?

There are no published SWE-bench Verified results for Llama-3.3-70B-Instruct and Claude Haiku 4.5 yet, so there is no like-for-like coding score. On overall capability, Claude Haiku 4.5 leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.

Which has the bigger context window?

Claude Haiku 4.5 has the largest context window at 200,000 tokens, against 128,000 for Llama-3.3-70B-Instruct. Maximum output per response: Llama-3.3-70B-Instruct up to 4,096, Claude Haiku 4.5 up to 64,000 tokens.

Which can read images, PDFs, audio or video?

Llama-3.3-70B-Instruct accepts text; Claude Haiku 4.5 accepts text, images and PDFs. Claude Haiku 4.5 handles the widest range of inputs.

Are any of these open source?

Llama-3.3-70B-Instruct publishes its weights and can be self-hosted; Claude Haiku 4.5 is proprietary.

Which is newer?

Claude Haiku 4.5 is the newest, released Oct 15, 2025. Llama-3.3-70B-Instruct came out Dec 6, 2024. Knowledge cutoff: Llama-3.3-70B-Instruct Dec 2023, Claude Haiku 4.5 Feb 28, 2025.

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 Oct 4, 2026.

05 — Keep comparing

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