Llama 3.3 70B Instruct vs MiMo-V2.6-Flash
MiMo-V2.6-Flash leads the LLM Stats Score 45.6 to 13.8. Llama 3.3 70B Instruct is 1.4x cheaper per token.
Meta · Xiaomi · Updated for 2026
Which is better?
MiMo-V2.6-Flash leads the overall LLM Stats Score 45.6 to 13.8, ranking #29 overall.
On price, Llama 3.3 70B Instruct is roughly 1.4x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
MiMo-V2.6-Flash also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Llama 3.3 70B Instruct
- cost matters — it's about 1.4x cheaper per token
Choose MiMo-V2.6-Flash
- overall performance matters — it scores 45.6 and ranks #29 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Sep 2026
At a glance
The differences that matter most.
Individual benchmarks
9 reported for Llama 3.3 70B Instruct · 16 for MiMo-V2.6-Flash
Llama 3.3 70B Instruct 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
Pricing Analysis
Price comparison per million tokens
For input processing, Llama 3.3 70B Instruct ($0.10/1M tokens) is 1.4x cheaper than MiMo-V2.6-Flash ($0.14/1M tokens).
For output processing, Llama 3.3 70B Instruct ($0.20/1M tokens) is 1.4x cheaper than MiMo-V2.6-Flash ($0.28/1M tokens).
In conclusion, MiMo-V2.6-Flash is more expensive than Llama 3.3 70B Instruct.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
MiMo-V2.6-Flash has 239.0B more parameters than Llama 3.3 70B Instruct, making it 341.4% larger.
Context Window
Maximum input and output token capacity
MiMo-V2.6-Flash accepts 1,048,576 input tokens compared to Llama 3.3 70B Instruct's 131,072 tokens. Only Llama 3.3 70B Instruct specifies output context (131,072 tokens).
Input capabilities
Documented input modalities across available providers
MiMo-V2.6-Flash supports multimodal inputs, whereas Llama 3.3 70B Instruct does not.
MiMo-V2.6-Flash can handle both text and other forms of data like images, making it suitable for multimodal applications.
Llama 3.3 70B Instruct
MiMo-V2.6-Flash
License
Usage and distribution terms
Llama 3.3 70B Instruct is licensed under Llama 3.3 Community License Agreement, while MiMo-V2.6-Flash uses MIT.
License differences may affect how you can use these models in commercial or open-source projects.
Llama 3.3 Community License Agreement
Open weights
MIT
Open weights
Release Timeline
When each model was launched
Llama 3.3 70B Instruct was released on 2024-12-06, while MiMo-V2.6-Flash was released on 2026-09-22.
MiMo-V2.6-Flash is 22 months newer than Llama 3.3 70B Instruct.
Dec 6, 2024
1.8 years ago
Sep 22, 2026
0 days ago
1.8yr newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Llama 3.3 70B Instruct is available from DeepInfra, Lambda, Hyperbolic, Groq, Sambanova, Cerebras, Bedrock, Together, Fireworks. MiMo-V2.6-Flash is available from Xiaomi.
Llama 3.3 70B Instruct
MiMo-V2.6-Flash
Outputs Comparison
Judge for yourself.
Run your own prompts against Llama 3.3 70B Instruct and MiMo-V2.6-Flash side-by-side, then vote on the output you prefer.
FAQ
Common questions about Llama 3.3 70B Instruct vs MiMo-V2.6-Flash.