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Llama 3.1 70B Instruct vs MiMo-V2.6-Pro

MiMo-V2.6-Pro leads the LLM Stats Score 49.8 to 7.6.

Meta · Xiaomi · Updated for 2026

Which is better?

MiMo-V2.6-Pro leads the overall LLM Stats Score 49.8 to 7.6, ranking #19 overall.

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

Choose Llama 3.1 70B Instruct

  • you want predictable pricing at $0.20/M input and $0.20/M output

Choose MiMo-V2.6-Pro

  • overall performance matters — it scores 49.8 and ranks #19 on LLM Stats
  • your work emphasizes reasoning and coding — 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
7.6
#289
49.8
#19
6.3
#291
45.2
#30
3.6
#218
41.8
#9
Cost, coverage & limits
Benchmark wins
Input price
$0.20 / M
— / M
Output price
$0.20 / M
— / M
Context window
128,000

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
Llama 3.1 70B Instruct
MiMo-V2.6-Pro
24.5#31
28.0#21
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

18 reported for Llama 3.1 70B Instruct · 3 for MiMo-V2.6-Pro

No common benchmarks found

Llama 3.1 70B 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

950.0B diff

MiMo-V2.6-Pro has 950.0B more parameters than Llama 3.1 70B Instruct, making it 1357.1% larger.

Meta
Llama 3.1 70B Instruct
70.0Bparameters
Xiaomi
MiMo-V2.6-Pro
1.0Tparameters
70.0B
Llama 3.1 70B Instruct
1020.0B
MiMo-V2.6-Pro

Context Window

Maximum input and output token capacity

Only Llama 3.1 70B Instruct specifies input context (128,000 tokens). Only Llama 3.1 70B Instruct specifies output context (128,000 tokens).

Meta
Llama 3.1 70B 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 3.1 70B 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 3.1 70B Instruct

Text
Images
Audio
Video

MiMo-V2.6-Pro

Text
Images
Audio
Video

License

Usage and distribution terms

Llama 3.1 70B Instruct is licensed under Llama 3.1 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 3.1 70B Instruct

Llama 3.1 Community License

Open weights

MiMo-V2.6-Pro

MIT

Open weights

Release Timeline

When each model was launched

Llama 3.1 70B Instruct was released on 2024-07-23, while MiMo-V2.6-Pro was released on 2026-09-22.

MiMo-V2.6-Pro is 26 months newer than Llama 3.1 70B Instruct.

Llama 3.1 70B Instruct

Jul 23, 2024

2.2 years ago

MiMo-V2.6-Pro

Sep 22, 2026

-1 days ago

2.2yr 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 3.1 70B Instruct and MiMo-V2.6-Pro side-by-side, then vote on the output you prefer.

Llama 3.1 70B Instruct
✓ Preferred
MiMo-V2.6-Pro
Open in Playground

FAQ

Common questions about Llama 3.1 70B Instruct vs MiMo-V2.6-Pro.

Which is better, Llama 3.1 70B Instruct or MiMo-V2.6-Pro?

MiMo-V2.6-Pro leads the LLM Stats Score 49.8 to 7.6. Llama 3.1 70B 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 3.1 70B Instruct compare to MiMo-V2.6-Pro in benchmarks?

Llama 3.1 70B Instruct scores GSM-8K (CoT): 95.1%, ARC-C: 94.8%, API-Bank: 90.0%, IFEval: 87.5%, Multilingual MGSM (CoT): 86.9%. 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 3.1 70B Instruct and MiMo-V2.6-Pro?

Llama 3.1 70B 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 3.1 70B Instruct and MiMo-V2.6-Pro?

Key differences include LLM Stats Score (7.6 vs 49.8), multimodal support (no vs yes), licensing (Llama 3.1 Community License vs MIT). See the full comparison above for benchmark-by-benchmark results.

Who makes Llama 3.1 70B Instruct and MiMo-V2.6-Pro?

Llama 3.1 70B Instruct is developed by Meta and MiMo-V2.6-Pro is developed by Xiaomi.