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Comparison · 2 models · Updated Oct 4, 2026

Qwen-VL OCR vs Llama-3.2-1B

Llama-3.2-1B comes out ahead, 55 to 36 on our weighted score, and it is the cheaper option too.

  1. Alibaba (Qwen)

    Qwen-VL OCR

    Released Oct 28, 2024

    36/100
    • ECI—
    • Price$0.72 / $0.72
    • Context34K
    Full specs Remove Qwen-VL OCR
  2. Our pick

    Meta

    Llama-3.2-1B

    Released Sep 25, 2024

    55/100
    • ECI102.0
    • Price$0.064 / $0.15
    • Context131K
    Full specs Remove Llama-3.2-1B

  3. Add a model

    Make it a three-way comparison.

01 — Verdict

Llama-3.2-1B is our pick

Llama-3.2-1B is the better all-round choice, scoring 55/100 against Qwen-VL OCR (36). It leads on price and context window. Qwen-VL OCR wins on inputs & features. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.

  • CapabilityNot enough dataNo independent benchmark covers every model here yet
  • Lowest priceLlama-3.2-1BLlama-3.2-1B $0.085 · Qwen-VL OCR $0.72 per 1M tokens (3:1 blend)
  • Longest contextLlama-3.2-1BLlama-3.2-1B 131,072 · Qwen-VL OCR 34,096 tokens
  • Widest inputsQwen-VL OCRQwen-VL OCR: Text, Images · Llama-3.2-1B: Text
  • Self-hostingLlama-3.2-1BPublishes downloadable weights (Llama 3.2 Community License)
How the score is built
MeasureWeightQwen-VL OCRLlama-3.2-1B
Price50%57100
Inputs & features30%250
Context window20%124
Overall100%36/10055/100

Left out because at least one model lacks the data: capability. The remaining weights were rescaled.

02 — Side by side

Every spec in one table

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

Qwen-VL OCR vs Llama-3.2-1B specifications side by side
SpecificationQwen-VL OCRAlibaba (Qwen)Llama-3.2-1BMeta
Capability
Capabilities Index (ECI)—102.0
ECI rank—#147 of 148
GPQA DiamondGraduate-level science questions—23.9%
OTIS Mock AIME 2024–2025Competition mathematics—0.6%
Price per million tokens
Input$0.72$0.064 (best)
Output$0.72$0.15 (best)
Cached input——
Blended (3:1)$0.72$0.085 (best)
Long-context rateSame rateSame rate
Price sourceOfficial Alibaba APIMedian of 2 providers
Limits
Context window34,096 tokens131,072 tokens (best)
Max output4,096 tokens8,192 tokens (best)
Inputs and features
TextYesYes
ImagesYesNo
PDFsNoNo
AudioNoNo
VideoNoNo
ReasoningNoNo
Tool callingNoNo
Structured outputNoNo
Availability
WeightsProprietaryOpenLlama 3.2 Community License
API model IDqwen-vl-ocr—
API providers12 (best)
ReleasedOct 28, 2024Sep 25, 2024
Knowledge cutoffApr 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.

  • Qwen-VL OCR$8.64
  • Llama-3.2-1B$0.936
04 — Questions

Which should you choose?

Which is better: Qwen-VL OCR or Llama-3.2-1B?

Llama-3.2-1B is the better all-round choice, scoring 55/100 against Qwen-VL OCR (36). It leads on price and context window. Qwen-VL OCR wins on inputs & features. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.

Which is cheaper, Qwen-VL OCR or Llama-3.2-1B?

Llama-3.2-1B is cheaper at $0.064 input / $0.15 output per million tokens (median across 2 API providers). Qwen-VL OCR costs $0.72 input / $0.72 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $0.085 per million tokens for Llama-3.2-1B versus $0.72 for Qwen-VL OCR (8.5× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers both models yet. Qwen-VL OCR has not been scored yet and Llama-3.2-1B has an ECI of 102.0.

Which is better for coding?

There are no published SWE-bench Verified results for Qwen-VL OCR and Llama-3.2-1B yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Qwen-VL OCR and Llama-3.2-1B does not support tool calling, which most coding agents need.

Which has the bigger context window?

Llama-3.2-1B has the largest context window at 131,072 tokens, against 34,096 for Qwen-VL OCR. Maximum output per response: Qwen-VL OCR up to 4,096, Llama-3.2-1B up to 8,192 tokens.

Which can read images, PDFs, audio or video?

Qwen-VL OCR accepts text and images; Llama-3.2-1B accepts text. Qwen-VL OCR 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; Qwen-VL OCR is proprietary.

Which is newer?

Qwen-VL OCR is the newest, released Oct 28, 2024. Llama-3.2-1B came out Sep 25, 2024. Knowledge cutoff: Qwen-VL OCR Apr 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 Oct 4, 2026.

05 — Keep comparing

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