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Comparison · 3 models · Updated Nov 2, 2026

PaddleOCR VL vs Voxtral Mini 3B 2507 vs Granite-4.0-H-Micro

Too close to call on our weighted score (PaddleOCR VL 62, Granite-4.0-H-Micro 62, Voxtral Mini 3B 2507 61). The right pick depends on what you value most.

  1. PaddlePaddle

    PaddleOCR VL

    Released Oct 16, 2025

    62/100
    • ECI—
    • Price$0.02 / $0.02
    • Context131K
  2. Mistral AI

    Voxtral Mini 3B 2507

    Released Jul 15, 2025

    61/100
    • ECI—
    • Price$0.04 / $0.04
    • Context33K
  3. IBM

    Granite-4.0-H-Micro

    Released Oct 2, 2025

    62/100
    • ECI—
    • Price$0.018 / $0.115
    • Context131K
01 — Verdict

Too close to call

It is close. Our weighted score puts them within a point (PaddleOCR VL 62/100, Granite-4.0-H-Micro 62/100, Voxtral Mini 3B 2507 61/100), so choose by what matters most for your work: PaddleOCR VL on price. 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 pricePaddleOCR VLPaddleOCR VL $0.02 · Voxtral Mini 3B 2507 $0.04 · Granite-4.0-H-Micro $0.042 per 1M tokens (3:1 blend)
  • Longest contextPaddleOCR VL and Granite-4.0-H-MicroPaddleOCR VL 131,072 · Granite-4.0-H-Micro 131,072 · Voxtral Mini 3B 2507 32,768 tokens
  • Widest inputsPaddleOCR VL and Voxtral Mini 3B 2507PaddleOCR VL: Text, Images · Voxtral Mini 3B 2507: Text, Audio · Granite-4.0-H-Micro: Text
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightPaddleOCR VLVoxtral Mini 3B 2507Granite-4.0-H-Micro
Price50%100100100
Inputs & features30%253525
Context window20%25025
Overall100%62/10061/10062/100

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.

PaddleOCR VL vs Voxtral Mini 3B 2507 vs Granite-4.0-H-Micro specifications side by side
SpecificationPaddleOCR VLPaddlePaddleVoxtral Mini 3B 2507Mistral AIGranite-4.0-H-MicroIBM
Capability
Capabilities Index (ECI)———
ECI rank———
Price per million tokens
Input$0.02$0.04$0.018 (best)
Output$0.02 (best)$0.04$0.115
Cached input———
Blended (3:1)$0.02 (best)$0.04$0.042
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 1 providersMedian of 2 providersMedian of 2 providers
Limits
Context window131,072 tokens (best)32,768 tokens131,072 tokens (best)
Max output16,384 tokens32,768 tokens131,072 tokens (best)
Inputs and features
TextYesYesYes
ImagesYesNoNo
PDFsNoNoNo
AudioNoYesNo
VideoNoNoNo
ReasoningNoNoNo
Tool callingNoYesYes
Structured outputNoNoNo
Availability
WeightsOpenApache-2.0OpenApache 2.0Open
API model ID———
API providers13 (best)2
ReleasedOct 16, 2025Jul 15, 2025Oct 2, 2025
Knowledge cutoff———
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.

  • PaddleOCR VL$0.24
  • Voxtral Mini 3B 2507$0.48
  • Granite-4.0-H-Micro$0.405
04 — Questions

Which should you choose?

Which is better: PaddleOCR VL, Voxtral Mini 3B 2507 or Granite-4.0-H-Micro?

It is close. Our weighted score puts them within a point (PaddleOCR VL 62/100, Granite-4.0-H-Micro 62/100, Voxtral Mini 3B 2507 61/100), so choose by what matters most for your work: PaddleOCR VL on price. 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, PaddleOCR VL, Voxtral Mini 3B 2507 or Granite-4.0-H-Micro?

PaddleOCR VL is cheaper at $0.02 input / $0.02 output per million tokens (median across 1 API provider). Voxtral Mini 3B 2507 costs $0.04 input / $0.04 output per million tokens (median across 2 API providers); Granite-4.0-H-Micro costs $0.018 input / $0.115 output per million tokens (median across 2 API providers). At a typical mix of three input tokens to one output token, that is $0.02 per million tokens for PaddleOCR VL versus $0.04 for Voxtral Mini 3B 2507 (2× as much) and $0.042 for Granite-4.0-H-Micro (2.1× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers all three models yet. PaddleOCR VL has not been scored yet, Voxtral Mini 3B 2507 has not been scored yet and Granite-4.0-H-Micro has not been scored yet.

Which is better for coding?

There are no published SWE-bench Verified results for PaddleOCR VL, Voxtral Mini 3B 2507 and Granite-4.0-H-Micro yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that PaddleOCR VL does not support tool calling, which most coding agents need.

Which has the bigger context window?

PaddleOCR VL and Granite-4.0-H-Micro have the largest context windows (131,072 and 131,072 tokens), against 32,768 for Voxtral Mini 3B 2507. Maximum output per response: PaddleOCR VL up to 16,384, Voxtral Mini 3B 2507 up to 32,768, Granite-4.0-H-Micro up to 131,072 tokens.

Which can read images, PDFs, audio or video?

PaddleOCR VL accepts text and images; Voxtral Mini 3B 2507 accepts text and audio; Granite-4.0-H-Micro accepts text. PaddleOCR VL handles the widest range of inputs.

Are any of these open source?

Yes, all three publish their weights (Apache-2.0 and Apache 2.0), so you can self-host them.

Which is newer?

PaddleOCR VL is the newest, released Oct 16, 2025. Granite-4.0-H-Micro came out Oct 2, 2025; Voxtral Mini 3B 2507 came out Jul 15, 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 Nov 2, 2026.