Devstral Small 1.1 vs GLM-5.3-Flash
GLM-5.3-Flash leads the LLM Stats Score 50.7 to 9.6. Devstral Small 1.1 is 1.6x cheaper per token.
Mistral AI · Zhipu AI · Updated for 2026
Which is better?
GLM-5.3-Flash leads the overall LLM Stats Score 50.7 to 9.6, ranking #16 overall.
On price, Devstral Small 1.1 is roughly 1.6x 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 Devstral Small 1.1
- cost matters — it's about 1.6x cheaper per token
Choose GLM-5.3-Flash
- overall performance matters — it scores 50.7 and ranks #16 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 Aug 2026
At a glance
The differences that matter most.
Individual benchmarks
1 reported for Devstral Small 1.1 · 15 for GLM-5.3-Flash
Devstral Small 1.1 and GLM-5.3-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, Devstral Small 1.1 ($0.10/1M tokens) is 1.5x cheaper than GLM-5.3-Flash ($0.15/1M tokens).
For output processing, Devstral Small 1.1 ($0.30/1M tokens) is 1.7x cheaper than GLM-5.3-Flash ($0.50/1M tokens).
In conclusion, GLM-5.3-Flash is more expensive than Devstral Small 1.1.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
GLM-5.3-Flash has 296.0B more parameters than Devstral Small 1.1, making it 1233.3% larger.
Context Window
Maximum input and output token capacity
GLM-5.3-Flash accepts 1,048,576 input tokens compared to Devstral Small 1.1's 128,000 tokens. GLM-5.3-Flash can generate longer responses up to 131,072 tokens, while Devstral Small 1.1 is limited to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
GLM-5.3-Flash supports multimodal inputs, whereas Devstral Small 1.1 does not.
GLM-5.3-Flash can handle both text and other forms of data like images, making it suitable for multimodal applications.
Devstral Small 1.1
GLM-5.3-Flash
License
Usage and distribution terms
Devstral Small 1.1 is licensed under Apache 2.0, while GLM-5.3-Flash uses MIT.
License differences may affect how you can use these models in commercial or open-source projects.
Apache 2.0
Open weights
MIT
Open weights
Release Timeline
When each model was launched
Devstral Small 1.1 was released on 2025-07-11, while GLM-5.3-Flash was released on 2026-08-26.
GLM-5.3-Flash is 14 months newer than Devstral Small 1.1.
Jul 11, 2025
1.2 years ago
Aug 26, 2026
1 weeks ago
1.1yr newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Devstral Small 1.1 is available from Mistral AI. GLM-5.3-Flash is available from DeepInfra, FriendliAI, Novita, ZAI.
Devstral Small 1.1
GLM-5.3-Flash
Outputs Comparison
Judge for yourself.
Run your own prompts against Devstral Small 1.1 and GLM-5.3-Flash side-by-side, then vote on the output you prefer.
FAQ
Common questions about Devstral Small 1.1 vs GLM-5.3-Flash.