GLM-5.3-Flash vs Mistral Small
Comparing GLM-5.3-Flash and Mistral Small across benchmarks, pricing, and capabilities.
Zhipu AI · Mistral AI · Updated for 2026
Which is better?
GLM-5.3-Flash and Mistral Small trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.
On price, GLM-5.3-Flash is roughly 1.3x 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 (1,000,000 input tokens), making it the stronger choice for long documents and large codebases.
Based on current benchmark, pricing, and model metadata for 2026.
Choose GLM-5.3-Flash
- cost matters — it's about 1.3x cheaper per token
- you process long inputs — it offers a 1,000,000 token context window
- you want the most recent training data — it shipped Aug 2026
Choose Mistral Small
- you want predictable pricing at $0.20/M input and $0.60/M output
At a glance
The differences that matter most.
Performance Benchmarks
Comparative analysis across standard metrics
GLM-5.3-Flash and Mistral Smalldon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Arena Performance
Playground indexes and blind preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GLM-5.3-Flash ($0.15/1M tokens) is 1.3x cheaper than Mistral Small ($0.20/1M tokens).
For output processing, GLM-5.3-Flash ($0.50/1M tokens) is 1.2x cheaper than Mistral Small ($0.60/1M tokens).
In conclusion, Mistral Small is more expensive than GLM-5.3-Flash.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
GLM-5.3-Flash has 298.0B more parameters than Mistral Small, making it 1354.5% larger.
Context Window
Maximum input and output token capacity
GLM-5.3-Flash accepts 1,000,000 input tokens compared to Mistral Small's 32,768 tokens. GLM-5.3-Flash can generate longer responses up to 131,072 tokens, while Mistral Small is limited to 32,768 tokens.
Input Capabilities
Supported data types and modalities
GLM-5.3-Flash supports multimodal inputs, whereas Mistral Small does not.
GLM-5.3-Flash can handle both text and other forms of data like images, making it suitable for multimodal applications.
GLM-5.3-Flash
Mistral Small
License
Usage and distribution terms
GLM-5.3-Flash is licensed under MIT, while Mistral Small uses Mistral Research License.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Mistral Research License
Open weights
Release Timeline
When each model was launched
GLM-5.3-Flash was released on 2026-08-26, while Mistral Small was released on 2024-09-17.
GLM-5.3-Flash is 24 months newer than Mistral Small.
Aug 26, 2026
0 days ago
1.9yr newerSep 17, 2024
1.9 years 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 ZAI. Mistral Small is available from Mistral AI.
GLM-5.3-Flash
Mistral Small
Outputs Comparison
Judge for yourself.
Run your own prompts against GLM-5.3-Flash and Mistral Small side-by-side, then vote on the output you prefer.
FAQ
Common questions about GLM-5.3-Flash vs Mistral Small.