DeepSeek-V4-Flash-0731 vs GLM-5.3
GLM-5.3 leads the LLM Stats Score 53.6 to 45.1. DeepSeek-V4-Flash-0731 is 19.1x cheaper per token.
DeepSeek · Zhipu AI · Updated for 2026
Which is better?
GLM-5.3 leads the overall LLM Stats Score 53.6 to 45.1, ranking #9 overall.
In the 6 individual benchmarks reported for both models, GLM-5.3 wins 6; this is a narrower head-to-head signal than the composite indexes.
On price, DeepSeek-V4-Flash-0731 is roughly 19.1x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
DeepSeek-V4-Flash-0731 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 DeepSeek-V4-Flash-0731
- cost matters — it's about 19.1x cheaper per token
- you process long inputs — it offers a 1,048,576 token context window
Choose GLM-5.3
- overall performance matters — it scores 53.6 and ranks #9 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you value its reported benchmark strengths — it wins 6 of 6 exact shared results
- you want the most recent training data — it shipped Aug 2026
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
9 reported for DeepSeek-V4-Flash-0731 · 17 for GLM-5.3
DeepSeek-V4-Flash-0731 outperforms in 0 benchmarks, while GLM-5.3 is better at 6 benchmarks (Agents' Last Exam, AutomationBench, CyberGym, NL2Repo, Terminal-Bench 2.1, Toolathlon).
GLM-5.3 significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V4-Flash-0731 ($0.09/1M tokens) is 15.6x cheaper than GLM-5.3 ($1.40/1M tokens).
For output processing, DeepSeek-V4-Flash-0731 ($0.18/1M tokens) is 24.4x cheaper than GLM-5.3 ($4.40/1M tokens).
In conclusion, GLM-5.3 is more expensive than DeepSeek-V4-Flash-0731.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
GLM-5.3 has 449.0B more parameters than DeepSeek-V4-Flash-0731, making it 147.7% larger.
Context Window
Maximum input and output token capacity
DeepSeek-V4-Flash-0731 accepts 1,048,576 input tokens compared to GLM-5.3's 1,000,000 tokens. DeepSeek-V4-Flash-0731 can generate longer responses up to 384,000 tokens, while GLM-5.3 is limited to 131,072 tokens.
License
Usage and distribution terms
DeepSeek-V4-Flash-0731 is licensed under MIT, while GLM-5.3 uses GLM-5.3 License.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
GLM-5.3 License
Open weights
Release Timeline
When each model was launched
DeepSeek-V4-Flash-0731 was released on 2026-07-31, while GLM-5.3 was released on 2026-08-14.
GLM-5.3 is 0 month newer than DeepSeek-V4-Flash-0731.
Jul 31, 2026
1 months ago
Aug 14, 2026
3 weeks ago
2w newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
DeepSeek-V4-Flash-0731 is available from DeepInfra, Novita, Fireworks. GLM-5.3 is available from FriendliAI, Novita, ZAI.
DeepSeek-V4-Flash-0731
GLM-5.3
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4-Flash-0731 and GLM-5.3 side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4-Flash-0731 vs GLM-5.3.