Model Comparison
DeepSeek-V4-Flash-Max vs GLM-5.1Which is better in 2026?
GLM-5.1 has a slight edge in benchmark performance. DeepSeek-V4-Flash-Max is 17.2x cheaper per token.
Verdict: DeepSeek-V4-Flash-Max vs GLM-5.1 — which is better?
DeepSeek-V4-Flash-Max (by DeepSeek) and GLM-5.1 (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.
DeepSeek-V4-Flash-Max outperforms in 4 benchmarks (GPQA, HMMT Feb 26, IMO-AnswerBench, Toolathlon), while GLM-5.1 is better at 6 benchmarks (BrowseComp, GDPval-AA, Humanity's Last Exam, MCP Atlas, SWE-Bench Pro, Terminal-Bench 2.0). GLM-5.1 has a slight edge in benchmark performance.
On price, DeepSeek-V4-Flash-Max is roughly 17.2x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
DeepSeek-V4-Flash-Max 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-Max if…
- cost matters — it's about 17.2x 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 Apr 2026
Choose GLM-5.1 if…
- you want the strongest raw capability — it leads on 6 of 10 shared benchmarks
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-V4-Flash-Max outperforms in 4 benchmarks (GPQA, HMMT Feb 26, IMO-AnswerBench, Toolathlon), while GLM-5.1 is better at 6 benchmarks (BrowseComp, GDPval-AA, Humanity's Last Exam, MCP Atlas, SWE-Bench Pro, Terminal-Bench 2.0).
GLM-5.1 has a slight edge in benchmark performance.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V4-Flash-Max ($0.10/1M tokens) is 14.0x cheaper than GLM-5.1 ($1.40/1M tokens).
For output processing, DeepSeek-V4-Flash-Max ($0.20/1M tokens) is 22.0x cheaper than GLM-5.1 ($4.40/1M tokens).
In conclusion, GLM-5.1 is more expensive than DeepSeek-V4-Flash-Max.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
GLM-5.1 has 470.0B more parameters than DeepSeek-V4-Flash-Max, making it 165.5% larger.
Context Window
Maximum input and output token capacity
DeepSeek-V4-Flash-Max accepts 1,048,576 input tokens compared to GLM-5.1's 200,000 tokens. GLM-5.1 can generate longer responses up to 128,000 tokens, while DeepSeek-V4-Flash-Max 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-Max was released on 2026-04-23, while GLM-5.1 was released on 2026-04-07.
DeepSeek-V4-Flash-Max is 1 month newer than GLM-5.1.
Apr 23, 2026
2 months ago
2w newerApr 7, 2026
3 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
DeepSeek-V4-Flash-Max is available from DeepInfra, DeepSeek, Fireworks, Novita. GLM-5.1 is available from FriendliAI, ZAI.
DeepSeek-V4-Flash-Max
GLM-5.1
Outputs Comparison
Key Takeaways
GLM-5.1
View detailsZhipu AI
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against DeepSeek-V4-Flash-Max and GLM-5.1 side-by-side, then vote on the output you prefer.
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FAQ
Common questions about DeepSeek-V4-Flash-Max vs GLM-5.1.