DeepSeek-V4-Flash-Max vs GLM-5
DeepSeek-V4-Flash-Max and GLM-5 are closely matched at 39.0 and 37.0 on the LLM Stats Score. DeepSeek-V4-Flash-Max is 13.8x cheaper per token.
DeepSeek · Zhipu AI · Updated for 2026
Which is better?
DeepSeek-V4-Flash-Max and GLM-5 are closely matched on the overall LLM Stats Score at 39.0 and 37.0.
In the 4 individual benchmarks reported for both models, DeepSeek-V4-Flash-Max wins 3; this is a narrower head-to-head signal than the composite indexes.
On price, DeepSeek-V4-Flash-Max is roughly 13.8x 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.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose DeepSeek-V4-Flash-Max
- you value its reported benchmark strengths — it wins 3 of 4 exact shared results
- cost matters — it's about 13.8x 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
- you want predictable pricing at $1.00/M input and $3.20/M output
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
19 reported for DeepSeek-V4-Flash-Max · 5 for GLM-5
DeepSeek-V4-Flash-Max outperforms in 3 benchmarks (MCP Atlas, SWE-Bench Verified, Terminal-Bench 2.0), while GLM-5 is better at 1 benchmark (BrowseComp).
DeepSeek-V4-Flash-Max shows notably better performance in the majority of 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-Max ($0.09/1M tokens) is 11.1x cheaper than GLM-5 ($1.00/1M tokens).
For output processing, DeepSeek-V4-Flash-Max ($0.18/1M tokens) is 17.8x cheaper than GLM-5 ($3.20/1M tokens).
In conclusion, GLM-5 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 has 460.0B more parameters than DeepSeek-V4-Flash-Max, making it 162.0% larger.
Context Window
Maximum input and output token capacity
DeepSeek-V4-Flash-Max accepts 1,048,576 input tokens compared to GLM-5's 200,000 tokens. DeepSeek-V4-Flash-Max can generate longer responses up to 1,048,576 tokens, while GLM-5 is limited to 128,000 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 was released on 2026-02-11.
DeepSeek-V4-Flash-Max is 2 months newer than GLM-5.
Apr 23, 2026
5 months ago
2mo newerFeb 11, 2026
7 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. GLM-5 is available from FriendliAI, ZAI.
DeepSeek-V4-Flash-Max
GLM-5
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4-Flash-Max and GLM-5 side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4-Flash-Max vs GLM-5.