DeepSeek-V4-Flash-Max vs GLM-5.2: Specs & Benchmark Comparison

DeepSeek-V4-Flash-Max is developed by DeepSeek, while GLM-5.2 comes from Zhipu AI. DeepSeek-V4-Flash-Max was released in April 2026, and GLM-5.2 followed 2 months later in June 2026. GLM-5.2 is the larger model at roughly 753 billion parameters, against 284 billion for DeepSeek-V4-Flash-Max.

The two models share 7 published benchmarks. GLM-5.2 leads on 6 of them, DeepSeek-V4-Flash-Max on 1. The widest gaps are on Humanity's Last Exam, where GLM-5.2 scores 54.7% against 45.1%; SWE-Bench Pro, where GLM-5.2 scores 62.1% against 52.6%. Averaged across everything we track, DeepSeek-V4-Flash-Max sits at 72.8% and GLM-5.2 at 60.9%.

DeepSeek-V4-Flash-Max is the cheaper API at $0.14 per million input tokens and $0.28 per million output tokens, roughly 10 times cheaper than GLM-5.2 at $1.40 and $4.40. Both accept a context window of about 1M tokens.

CharacteristicDeepSeek-V4-Flash-MaxGLM-5.2
CompanyDeepSeekZhipu AI
Release DateApril 23, 2026June 16, 2026
Parameters284B753B
MultimodalNoNo
Context (input)1.0M1.0M
Context (output)393K131K
Input Price / 1M$0.14$1.40
Output Price / 1M$0.28$4.40
Average Score72.8%60.9%
Benchmarks
Humanity's Last Exam45.1%54.7%
SWE-Bench Pro52.6%62.1%
MCP Atlas69.0%76.8%
IMO-AnswerBench88.0%91.0%
GPQA88.1%91.0%
HMMT Feb 2695.0%92.5%
Toolathlon47.8%48.2%

Visual Benchmark Comparison

DeepSeek-V4-Flash-Max
GLM-5.2
Humanity's Last Exam0.5 vs 0.5
0.5
0.5
SWE-Bench Pro0.5 vs 0.6
0.5
0.6
MCP Atlas0.7 vs 0.8
0.7
0.8
IMO-AnswerBench0.9 vs 0.9
0.9
0.9
GPQA0.9 vs 0.9
0.9
0.9
HMMT Feb 260.9 vs 0.9
0.9
0.9
Toolathlon0.5 vs 0.5
0.5
0.5

Verdict

GLM-5.2 leads in 2 out of 4 comparison categories.

Overall Performance

Both models show comparable average scores: DeepSeek-V4-Flash-Max — 0.7, GLM-5.2 — 0.6.

API Cost

DeepSeek-V4-Flash-Max is 13.8x cheaper: input $0.14/1M vs $1.40/1M tokens.

Context Window

GLM-5.2 supports a larger context: 1M vs 1M tokens.

Recency

GLM-5.2 is newer: released 6/16/2026 vs 4/23/2026.

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Frequently Asked Questions

Which is better for coding — DeepSeek-V4-Flash-Max or GLM-5.2?
Direct comparison on the SWE-Bench benchmark is not available. We recommend reviewing other metrics on the comparison page.
Which model is cheaper — DeepSeek-V4-Flash-Max or GLM-5.2?
DeepSeek-V4-Flash-Max is cheaper for input: $0.14 per 1M tokens vs $1.40.
Which has a larger context window — DeepSeek-V4-Flash-Max or GLM-5.2?
GLM-5.2 supports a larger context: 1,048,576 tokens vs 1,000,000.

The DeepSeek-V4-Flash-Max and GLM-5.2 comparison is updated for 2026. Data includes benchmark results, API pricing, context window size and other specifications. For more detailed information, visit the DeepSeek-V4-Flash-Max or GLM-5.2 page. See also the complete list of AI model comparisons.