Model Comparison
DeepSeek-V4-Flash-0731 vs GLM-4.5Which is better in 2026?
Comparing DeepSeek-V4-Flash-0731 and GLM-4.5 across benchmarks, pricing, and capabilities.
Verdict: DeepSeek-V4-Flash-0731 vs GLM-4.5 — which is better?
DeepSeek-V4-Flash-0731 (by DeepSeek) and GLM-4.5 (by Zhipu AI) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.
On price, DeepSeek-V4-Flash-0731 is roughly 6.2x 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.
Choose DeepSeek-V4-Flash-0731 if…
- cost matters — it's about 6.2x 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 Jul 2026
Choose GLM-4.5 if…
- you want predictable pricing at $0.40/M input and $1.60/M output
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-V4-Flash-0731 and GLM-4.5don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V4-Flash-0731 ($0.09/1M tokens) is 4.4x cheaper than GLM-4.5 ($0.40/1M tokens).
For output processing, DeepSeek-V4-Flash-0731 ($0.18/1M tokens) is 8.9x cheaper than GLM-4.5 ($1.60/1M tokens).
In conclusion, GLM-4.5 is more expensive than DeepSeek-V4-Flash-0731.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
GLM-4.5 has 51.0B more parameters than DeepSeek-V4-Flash-0731, making it 16.8% larger.
Context Window
Maximum input and output token capacity
DeepSeek-V4-Flash-0731 accepts 1,048,576 input tokens compared to GLM-4.5's 131,072 tokens. GLM-4.5 can generate longer responses up to 131,072 tokens, while DeepSeek-V4-Flash-0731 is limited to 65,536 tokens.
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
DeepSeek-V4-Flash-0731 was released on 2026-07-31, while GLM-4.5 was released on 2025-07-28.
DeepSeek-V4-Flash-0731 is 12 months newer than GLM-4.5.
Jul 31, 2026
3 days ago
1.0yr newerJul 28, 2025
1.0 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
DeepSeek-V4-Flash-0731 is available from DeepInfra, Fireworks, Novita. GLM-4.5 is available from DeepInfra, Fireworks, Novita.
DeepSeek-V4-Flash-0731
GLM-4.5
Outputs Comparison
Key Takeaways
GLM-4.5
View detailsZhipu AI
No standout differentiators in the data we have for this pair.
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against DeepSeek-V4-Flash-0731 and GLM-4.5 side-by-side, then vote on the output you prefer.
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FAQ
Common questions about DeepSeek-V4-Flash-0731 vs GLM-4.5.