The AI arena is free today

Open Superagent

DeepSeek R1 Distill Llama 70B vs MiMo-V2.6-Flash

MiMo-V2.6-Flash leads the LLM Stats Score 45.7 to 14.5.

DeepSeek · Xiaomi · Updated for 2026

Which is better?

MiMo-V2.6-Flash leads the overall LLM Stats Score 45.7 to 14.5, ranking #29 overall.

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

Choose DeepSeek R1 Distill Llama 70B

  • you want predictable pricing at $0.10/M input and $0.40/M output

Choose MiMo-V2.6-Flash

  • overall performance matters — it scores 45.7 and ranks #29 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.

DeepSeek R1 Distill Llama 70B
DeepSeek
MiMo-V2.6-Flash
Xiaomi
Core performance indexes
LLM Stats Score
14.5
#238
45.7
#29
Reasoning
14.7
#230
43.2
#42
Coding
8.6
#182
36.6
#21
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.10 / M
— / M
Output price
$0.40 / M
— / M
Context window
128,000
—

Individual benchmarks

4 reported for DeepSeek R1 Distill Llama 70B · 16 for MiMo-V2.6-Flash

No common benchmarks found

DeepSeek R1 Distill Llama 70B and MiMo-V2.6-Flashdon'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

238.4B diff

MiMo-V2.6-Flash has 238.4B more parameters than DeepSeek R1 Distill Llama 70B, making it 337.7% larger.

DeepSeek
DeepSeek R1 Distill Llama 70B
70.6Bparameters
Xiaomi
MiMo-V2.6-Flash
309.0Bparameters
70.6B
DeepSeek R1 Distill Llama 70B
309.0B
MiMo-V2.6-Flash

Context Window

Maximum input and output token capacity

Only DeepSeek R1 Distill Llama 70B specifies input context (128,000 tokens). Only DeepSeek R1 Distill Llama 70B specifies output context (128,000 tokens).

DeepSeek
DeepSeek R1 Distill Llama 70B
Input128,000 tokens
Output128,000 tokens
Xiaomi
MiMo-V2.6-Flash
Input- tokens
Output- tokens
Mon Sep 21 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

MiMo-V2.6-Flash supports multimodal inputs, whereas DeepSeek R1 Distill Llama 70B does not.

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

DeepSeek R1 Distill Llama 70B

Text
Images
Audio
Video

MiMo-V2.6-Flash

Text
Images
Audio
Video

License

Usage and distribution terms

Both models are licensed under MIT.

Both models share the same licensing terms, providing consistent usage rights.

DeepSeek R1 Distill Llama 70B

MIT

Open weights

MiMo-V2.6-Flash

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek R1 Distill Llama 70B was released on 2025-01-20, while MiMo-V2.6-Flash was released on 2026-09-22.

MiMo-V2.6-Flash is 20 months newer than DeepSeek R1 Distill Llama 70B.

DeepSeek R1 Distill Llama 70B

Jan 20, 2025

1.7 years ago

MiMo-V2.6-Flash

Sep 22, 2026

-1 days ago

1.7yr 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 DeepSeek R1 Distill Llama 70B and MiMo-V2.6-Flash side-by-side, then vote on the output you prefer.

DeepSeek R1 Distill Llama 70B
✓ Preferred
MiMo-V2.6-Flash
Open in Playground

FAQ

Common questions about DeepSeek R1 Distill Llama 70B vs MiMo-V2.6-Flash.

Which is better, DeepSeek R1 Distill Llama 70B or MiMo-V2.6-Flash?

MiMo-V2.6-Flash leads the LLM Stats Score 45.7 to 14.5. DeepSeek R1 Distill Llama 70B is made by DeepSeek and MiMo-V2.6-Flash is made by Xiaomi. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does DeepSeek R1 Distill Llama 70B compare to MiMo-V2.6-Flash in benchmarks?

DeepSeek R1 Distill Llama 70B scores MATH-500: 94.5%, AIME 2024: 86.7%, GPQA: 65.2%, LiveCodeBench: 57.5%. MiMo-V2.6-Flash scores CyberGym: 95.1%, Terminal-Bench 2.1: 87.6%, OSWorld-Verified: 80.8%, MiMo Cyber Bench: 77.2%, Toolathlon-Verified: 73.6%.

What are the context window sizes for DeepSeek R1 Distill Llama 70B and MiMo-V2.6-Flash?

DeepSeek R1 Distill Llama 70B supports 128K tokens and MiMo-V2.6-Flash 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 DeepSeek R1 Distill Llama 70B and MiMo-V2.6-Flash?

Key differences include LLM Stats Score (14.5 vs 45.7), multimodal support (no vs yes). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek R1 Distill Llama 70B and MiMo-V2.6-Flash?

DeepSeek R1 Distill Llama 70B is developed by DeepSeek and MiMo-V2.6-Flash is developed by Xiaomi.

Related comparisons