Model comparison

DeepSeek V4 Flash vs GLM-5

Data verified July 23, 2026

Head-to-head evidence from 14 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

DeepSeek V4 Flash

DeepSeek

58.88/100

Margin

7.2pts

winning →

GLM-5

Z.AI

66.06/100

0 category wins4 category wins

Public leaderboard positions: DeepSeek V4 Flash #61 (Estimated); GLM-5 #28 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. DeepSeek V4 Flash and GLM-5 share 14 comparable benchmark results. 4 of 8 categories are comparable. 8 results are unique to DeepSeek V4 Flash; 35 to GLM-5.

Updated July 23, 2026

Shared results: 14
DeepSeek V4 Flash only: 8
GLM-5 only: 35
Comparable categories: 4 / 8

Pick GLM-5 if you want the stronger benchmark profile. DeepSeek V4 Flash only becomes the better choice if you want the cheaper token bill or you need the larger 1M context window.

Confidence note. This is a partial-evidence comparison with 14 shared benchmark results across 5 evidence categories; 4 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.

Why this result

GLM-5 is clearly ahead on the BenchAlign aggregate, 66.06 to 58.88. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

GLM-5's sharpest advantage is in knowledge, where it averages 66.4 against 38.8. The single biggest benchmark swing on the page is HMMT Feb 2026, 40.8% to 86.4%.

GLM-5 is also the more expensive model on tokens at $1.00 input / $3.20 output per 1M tokens, versus $0.14 input / $0.28 output per 1M tokens for DeepSeek V4 Flash. That is roughly 11.4x on output cost alone. DeepSeek V4 Flash gives you the larger context window at 1M, compared with 200K for GLM-5.

Category breakdown

Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.

Category scores and score margins for DeepSeek V4 Flash and GLM-5
Category	DeepSeek V4 Flash	Δ	GLM-5
Knowledge	DeepSeek V4 Flash38.8	Margin→ 27.6	GLM-566.4
Math	DeepSeek V4 Flash40.8	Margin→ 15.5	GLM-556.3
Agentic	DeepSeek V4 Flash49.1	Margin→ 7.1	GLM-556.2
Coding	DeepSeek V4 Flash64.2	Margin→ 2.1	GLM-566.3
Reasoning	DeepSeek V4 FlashNot measured	MarginNo overlap	GLM-560.8
Multilingual	DeepSeek V4 FlashNot measured	MarginNo overlap	GLM-583.1
Inst. Following	DeepSeek V4 FlashNot measured	MarginNo overlap	GLM-592.6

Decisive benchmark drivers

The largest measured benchmark gaps in this matchup, with exact reported values.

A · DeepSeek V4 FlashB · GLM-5

HMMT Feb 2026
Math
Source ↗
A 40.8%B 86.4%
Winner: GLM-5Δ 45.6
HMMT Feb 2026: DeepSeek V4 Flash scored 40.8%; GLM-5 scored 86.4%. GLM-5 wins this benchmark.
HLE
Knowledge
Source ↗
A 8.1%B 50.4%
Winner: GLM-5Δ 42.3
HLE: DeepSeek V4 Flash scored 8.1%; GLM-5 scored 50.4%. GLM-5 wins this benchmark.
GPQA
Knowledge
Source ↗
A 71.2%B 86%
Winner: GLM-5Δ 14.8
GPQA: DeepSeek V4 Flash scored 71.2%; GLM-5 scored 86%. GLM-5 wins this benchmark.
Terminal-Bench 2.0
Agentic
Source ↗
A 49.1%B 56.2%
Winner: GLM-5Δ 7.1
Terminal-Bench 2.0: DeepSeek V4 Flash scored 49.1%; GLM-5 scored 56.2%. GLM-5 wins this benchmark.
SWE-bench Pro
Coding
Source ↗
A 49.1%B 55.1%
Winner: GLM-5Δ 6
SWE-bench Pro: DeepSeek V4 Flash scored 49.1%; GLM-5 scored 55.1%. GLM-5 wins this benchmark.

Operational comparison

Runtime and commercial metrics are compared only when both models have a complete sourced value.

Metric	DeepSeek V4 Flash	GLM-5	Comparison
Input / output priceUSD per 1M tokens	DeepSeek V4 Flash$0.14 input / $0.28 output	GLM-5$1 input / $3.2 output	DeepSeek V4 Flash has the lower combined listed price.
Generation speedtokens per second	DeepSeek V4 FlashNot available	GLM-574 tok/s	A complete speed comparison is not available.
First-answer latencyseconds to first token	DeepSeek V4 FlashNot available	GLM-51.64 s	A complete latency comparison is not available.
Context windowmaximum listed tokens	DeepSeek V4 Flash1M	GLM-5200K	DeepSeek V4 Flash lists the larger context window.

Benchmark Deep Dive

AgenticGLM-5 wins

13 benchmarks

Benchmark	DeepSeek V4 Flash	GLM-5	Result
Terminal-Bench 2.0Source	49.1%	56.2%	GLM-5 leads
MCP AtlasSource	64%	31.1%	DeepSeek V4 Flash leads
ToolathlonSource	40.7%	38%	DeepSeek V4 Flash leads
Claw-EvalSource	57.8%	57.7%	DeepSeek V4 Flash leads
Gert LabsSource	54.35%	50.99%	DeepSeek V4 Flash leads
QwenClawBenchSource	—	54.1%	Not comparable
τ³-bench resultsSource	—	65.6%	Not comparable
DeepPlanningSource	—	14.6%	Not comparable
MCP-TasksSource	—	60.8%	Not comparable
WideResearchSource	—	69.8%	Not comparable
τ²-bench resultsSource	—	98.2%	Not comparable
CyberGymSource	—	43.2%	Not comparable
APEX-Agents-AASource	—	14.5%	Not comparable

CodingGLM-5 wins

8 benchmarks

Benchmark	DeepSeek V4 Flash	GLM-5	Result
SWE-bench VerifiedSource	73.7%	77.8%	GLM-5 leads
SWE-bench ProSource	49.1%	55.1%	GLM-5 leads
SWE MultilingualSource	69.7%	73.3%	GLM-5 leads
Terminal-Bench 2.0Source	49.1%	—	Not comparable
SWE-bench Verified*Source	—	72.8%	Not comparable
SWE-RebenchSource	—	62.8%	Not comparable
React Native EvalsSource	—	74.8%	Not comparable
AA-SciCodeSource	—	46.2%	Not comparable

Reasoning

6 benchmarks

Benchmark	DeepSeek V4 Flash	GLM-5	Result
MRCR 1MSource	37.5%	—	Not comparable
CorpusQA 1MSource	15.5%	—	Not comparable
LongBench v2Source	—	60.8%	Not comparable
AI-NeedleSource	—	63.3%	Not comparable
AA-LCRSource	—	63.3%	Not comparable
CritPtSource	—	2.0%	Not comparable

KnowledgeGLM-5 wins

14 benchmarks

Benchmark	DeepSeek V4 Flash	GLM-5	Result
MMLU-ProSource	83%	85.7%	GLM-5 leads
SimpleQASource	23.1%	—	Not comparable
Chinese-SimpleQASource	71.5%	—	Not comparable
GPQASource	71.2%	86%	GLM-5 leads
GPQA-DSource	71.2%	86.0%	GLM-5 leads
HLESource	8.1%	50.4%	GLM-5 leads
SuperGPQASource	—	66.8%	Not comparable
MMLU-Pro (Arcee)Source	—	85.8%	Not comparable
Artificial Analysis Intelligence IndexSource	—	39.5%	Not comparable
AA-GPQA DiamondSource	—	82.0%	Not comparable
AA-HLESource	—	27.2%	Not comparable
AA-Omniscience IndexSource	—	2.0%	Not comparable
AA-Omniscience AccuracySource	—	26.9%	Not comparable
AA-Omniscience Hallucination RateSource	—	34.0%	Not comparable

MathGLM-5 wins

11 benchmarks

Benchmark	DeepSeek V4 Flash	GLM-5	Result
HMMT Feb 2026Source	40.8%	86.4%	GLM-5 leads
IMOAnswerBenchSource	41.9%	—	Not comparable
ApexSource	1.0%	—	Not comparable
Apex ShortlistSource	9.3%	—	Not comparable
AIME26Source	—	95.8%	Not comparable
AIME25 (Arcee)Source	—	93.3%	Not comparable
HMMT Feb 2025Source	—	97.5%	Not comparable
HMMT Nov 2025Source	—	96.9%	Not comparable
MMAnswerBenchSource	—	82.5%	Not comparable
FrontierMath v2 (Tiers 1-3)Source	—	16.434%	Not comparable
FrontierMath v2 (Tier 4)Source	—	2.100%	Not comparable

Multilingual

2 benchmarks

Benchmark	DeepSeek V4 Flash	GLM-5	Result
MMLU-ProXSource	—	83.1%	Not comparable
NOVA-63Source	—	55.1%	Not comparable

Multimodal

1 benchmarks

Benchmark	DeepSeek V4 Flash	GLM-5	Result
Design Arena WebsiteSource	1238	1278	GLM-5 leads

Inst. Following

2 benchmarks

Benchmark	DeepSeek V4 Flash	GLM-5	Result
IFEvalSource	—	92.6%	Not comparable
AA-IFBenchSource	—	72.3%	Not comparable

Frequently Asked Questions (5)

Which is better, DeepSeek V4 Flash or GLM-5?

GLM-5 is ahead on BenchLM's BenchAlign leaderboard, 66.06 to 58.88. The biggest single separator in this matchup is HMMT Feb 2026, where the scores are 40.8% and 86.4%.

Which is better for knowledge tasks, DeepSeek V4 Flash or GLM-5?

GLM-5 has the edge for knowledge tasks in this comparison, averaging 66.4 versus 38.8. Inside this category, HLE is the benchmark that creates the most daylight between them.

Which is better for coding, DeepSeek V4 Flash or GLM-5?

GLM-5 has the edge for coding in this comparison, averaging 66.3 versus 64.2. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.

Which is better for math, DeepSeek V4 Flash or GLM-5?

GLM-5 has the edge for math in this comparison, averaging 56.3 versus 40.8. Inside this category, HMMT Feb 2026 is the benchmark that creates the most daylight between them.

Which is better for agentic tasks, DeepSeek V4 Flash or GLM-5?

GLM-5 has the edge for agentic tasks in this comparison, averaging 56.2 versus 49.1. Inside this category, MCP Atlas is the benchmark that creates the most daylight between them.

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