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Llama 3.2 3B Instruct vs MiMo-V2.6-Pro

MiMo-V2.6-Pro leads the LLM Stats Score 49.8 to -6.1.

Meta · Xiaomi · Updated for 2026

Which is better?

MiMo-V2.6-Pro leads the overall LLM Stats Score 49.8 to -6.1, ranking #19 overall.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose Llama 3.2 3B Instruct

  • you want predictable pricing at $0.01/M input and $0.02/M output

Choose MiMo-V2.6-Pro

  • overall performance matters — it scores 49.8 and ranks #19 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you want the most recent training data — it shipped Sep 2026

At a glance

The differences that matter most.

Core performance indexes
-6.1
#363
49.8
#19
-6.7
#357
45.2
#30
Cost, coverage & limits
Benchmark wins
Input price
$0.01 / M
— / M
Output price
$0.02 / M
— / M
Context window
128,000

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
Llama 3.2 3B Instruct
MiMo-V2.6-Pro
4.7#158
28.0#21
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

15 reported for Llama 3.2 3B Instruct · 3 for MiMo-V2.6-Pro

No common benchmarks found

Llama 3.2 3B Instruct and MiMo-V2.6-Prodon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

1016.8B diff

MiMo-V2.6-Pro has 1016.8B more parameters than Llama 3.2 3B Instruct, making it 31675.7% larger.

Meta
Llama 3.2 3B Instruct
3.2Bparameters
Xiaomi
MiMo-V2.6-Pro
1.0Tparameters
3.2B
Llama 3.2 3B Instruct
1020.0B
MiMo-V2.6-Pro

Context Window

Maximum input and output token capacity

Only Llama 3.2 3B Instruct specifies input context (128,000 tokens). Only Llama 3.2 3B Instruct specifies output context (128,000 tokens).

Meta
Llama 3.2 3B Instruct
Input128,000 tokens
Output128,000 tokens
Xiaomi
MiMo-V2.6-Pro
Input- tokens
Output- tokens
Tue Sep 22 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

MiMo-V2.6-Pro supports multimodal inputs, whereas Llama 3.2 3B Instruct does not.

MiMo-V2.6-Pro can handle both text and other forms of data like images, making it suitable for multimodal applications.

Llama 3.2 3B Instruct

Text
Images
Audio
Video

MiMo-V2.6-Pro

Text
Images
Audio
Video

License

Usage and distribution terms

Llama 3.2 3B Instruct is licensed under Llama 3.2 Community License, while MiMo-V2.6-Pro uses MIT.

License differences may affect how you can use these models in commercial or open-source projects.

Llama 3.2 3B Instruct

Llama 3.2 Community License

Open weights

MiMo-V2.6-Pro

MIT

Open weights

Release Timeline

When each model was launched

Llama 3.2 3B Instruct was released on 2024-09-25, while MiMo-V2.6-Pro was released on 2026-09-22.

MiMo-V2.6-Pro is 24 months newer than Llama 3.2 3B Instruct.

Llama 3.2 3B Instruct

Sep 25, 2024

2.0 years ago

MiMo-V2.6-Pro

Sep 22, 2026

-1 days ago

2.0yr newer

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Judge for yourself.

Run your own prompts against Llama 3.2 3B Instruct and MiMo-V2.6-Pro side-by-side, then vote on the output you prefer.

Llama 3.2 3B Instruct
✓ Preferred
MiMo-V2.6-Pro
Open in Playground

FAQ

Common questions about Llama 3.2 3B Instruct vs MiMo-V2.6-Pro.

Which is better, Llama 3.2 3B Instruct or MiMo-V2.6-Pro?

MiMo-V2.6-Pro leads the LLM Stats Score 49.8 to -6.1. Llama 3.2 3B Instruct is made by Meta and MiMo-V2.6-Pro is made by Xiaomi. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does Llama 3.2 3B Instruct compare to MiMo-V2.6-Pro in benchmarks?

Llama 3.2 3B Instruct scores NIH/Multi-needle: 84.7%, ARC-C: 78.6%, GSM8k: 77.7%, IFEval: 77.4%, HellaSwag: 69.8%. MiMo-V2.6-Pro scores DeepSWE 1.1: 71.9%, MiMo Coding Bench: 63.2%, Program Bench: 26.5%.

What are the context window sizes for Llama 3.2 3B Instruct and MiMo-V2.6-Pro?

Llama 3.2 3B Instruct supports 128K tokens and MiMo-V2.6-Pro supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Llama 3.2 3B Instruct and MiMo-V2.6-Pro?

Key differences include LLM Stats Score (-6.1 vs 49.8), multimodal support (no vs yes), licensing (Llama 3.2 Community License vs MIT). See the full comparison above for benchmark-by-benchmark results.

Who makes Llama 3.2 3B Instruct and MiMo-V2.6-Pro?

Llama 3.2 3B Instruct is developed by Meta and MiMo-V2.6-Pro is developed by Xiaomi.