GLM-5.3-Flash vs Mistral Large 3
GLM-5.3-Flash leads the LLM Stats Score 51.6 to 11.0. GLM-5.3-Flash is 11.6x cheaper per token.
Zhipu AI · Mistral AI · Updated for 2026
Which is better?
GLM-5.3-Flash leads the overall LLM Stats Score 51.6 to 11.0, ranking #11 overall.
On price, GLM-5.3-Flash is roughly 11.6x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GLM-5.3-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 GLM-5.3-Flash
- overall performance matters — it scores 51.6 and ranks #11 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- cost matters — it's about 11.6x 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 Aug 2026
Choose Mistral Large 3
- you want predictable pricing at $2.00/M input and $5.00/M output
At a glance
The differences that matter most.
Individual benchmarks
15 reported for GLM-5.3-Flash · 8 for Mistral Large 3
GLM-5.3-Flash and Mistral Large 3don'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-5.3-Flash ($0.15/1M tokens) is 13.3x cheaper than Mistral Large 3 ($2.00/1M tokens).
For output processing, GLM-5.3-Flash ($0.50/1M tokens) is 10.0x cheaper than Mistral Large 3 ($5.00/1M tokens).
In conclusion, Mistral Large 3 is more expensive than GLM-5.3-Flash.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Mistral Large 3 has 355.0B more parameters than GLM-5.3-Flash, making it 110.9% larger.
Context Window
Maximum input and output token capacity
GLM-5.3-Flash accepts 1,048,576 input tokens compared to Mistral Large 3's 128,000 tokens. GLM-5.3-Flash can generate longer responses up to 131,072 tokens, while Mistral Large 3 is limited to 8,192 tokens.
Input capabilities
Documented input modalities across available providers
Both GLM-5.3-Flash and Mistral Large 3 support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
GLM-5.3-Flash
Mistral Large 3
License
Usage and distribution terms
GLM-5.3-Flash is licensed under MIT, while Mistral Large 3 uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
GLM-5.3-Flash was released on 2026-08-26, while Mistral Large 3 was released on 2025-09-01.
GLM-5.3-Flash is 12 months newer than Mistral Large 3.
Aug 26, 2026
2 days ago
11mo newerSep 1, 2025
12 months ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
GLM-5.3-Flash is available from DeepInfra, Novita, ZAI. Mistral Large 3 is available from Mistral AI.
GLM-5.3-Flash
Mistral Large 3
Outputs Comparison
Judge for yourself.
Run your own prompts against GLM-5.3-Flash and Mistral Large 3 side-by-side, then vote on the output you prefer.
FAQ
Common questions about GLM-5.3-Flash vs Mistral Large 3.