GLM-4.6 vs MiMo-V2.6-Pro
MiMo-V2.6-Pro leads the LLM Stats Score 49.8 to 29.0. MiMo-V2.6-Pro is 1.6x cheaper per token.
Zhipu AI · Xiaomi · Updated for 2026
Which is better?
MiMo-V2.6-Pro leads the overall LLM Stats Score 49.8 to 29.0, ranking #19 overall.
On price, MiMo-V2.6-Pro is roughly 1.6x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
MiMo-V2.6-Pro 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 GLM-4.6
- you want predictable pricing at $0.50/M input and $2.00/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
- cost matters — it's about 1.6x cheaper per token
- 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
7 reported for GLM-4.6 · 18 for MiMo-V2.6-Pro
GLM-4.6 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
Pricing Analysis
Price comparison per million tokens
For input processing, GLM-4.6 ($0.50/1M tokens) is 1.1x more expensive than MiMo-V2.6-Pro ($0.43/1M tokens).
For output processing, GLM-4.6 ($2.00/1M tokens) is 2.3x more expensive than MiMo-V2.6-Pro ($0.87/1M tokens).
In conclusion, GLM-4.6 is more expensive than MiMo-V2.6-Pro.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
MiMo-V2.6-Pro has 663.0B more parameters than GLM-4.6, making it 185.7% larger.
Context Window
Maximum input and output token capacity
MiMo-V2.6-Pro accepts 1,048,576 input tokens compared to GLM-4.6's 202,752 tokens. Only GLM-4.6 specifies output context (202,752 tokens).
Input capabilities
Documented input modalities across available providers
Both GLM-4.6 and MiMo-V2.6-Pro support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
GLM-4.6
MiMo-V2.6-Pro
License
Usage and distribution terms
Both models are licensed under MIT.
Both models share the same licensing terms, providing consistent usage rights.
MIT
Open weights
MIT
Open weights
Release Timeline
When each model was launched
GLM-4.6 was released on 2025-09-30, while MiMo-V2.6-Pro was released on 2026-09-22.
MiMo-V2.6-Pro is 12 months newer than GLM-4.6.
Sep 30, 2025
11 months ago
Sep 22, 2026
0 days ago
11mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
GLM-4.6 is available from DeepInfra, Fireworks. MiMo-V2.6-Pro is available from Xiaomi.
GLM-4.6
MiMo-V2.6-Pro
Outputs Comparison
Judge for yourself.
Run your own prompts against GLM-4.6 and MiMo-V2.6-Pro side-by-side, then vote on the output you prefer.
FAQ
Common questions about GLM-4.6 vs MiMo-V2.6-Pro.