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DeepSeek V4 Flash 0731 vs GLM 4.7

GLM 4.7 leads DeepSeek V4 Flash 0731 on coding, 55.1 to 51.8 on the Vibe Coding Index, and DeepSeek V4 Flash 0731 costs 7.9x less per output token ($0.28 vs $2.20 per million). Updated October 21, 2026; 30 benchmarks have a result for both.

Replace DeepSeek V4 Flash 0731 Replace GLM 4.7
DeepSeek V4 Flash 0731DeepSeek
Coding
51.8
Overall
55.2
Output $/M
$0.28
27
GLM 4.7Z.ai
Coding
55.1
Overall
56.9
Output $/M
$2.20
3
vs boards won of 30 shared

DeepSeek V4 Flash 0731 or GLM 4.7: which to pick

Pick GLM 4.7 for coding: it scores 55.1 on the Vibe Coding Index against 51.8 for DeepSeek V4 Flash 0731, though on 2 benchmarks against 4.

Pick DeepSeek V4 Flash 0731 for output tokens 7.9x cheaper ($0.28 vs $2.20 per million) and a lower cost per solved task ($0.01 against $0.29).

Model ADeepSeek V4 Flash 0731DeepSeek51.8/1004 independent benchmarks$0.01 per solved taskModel BGLM 4.7Z.ai55.1/1002 independent benchmarks$0.29 per solved task
Shared results
30
DeepSeek V4 Flash 0731 only
25
GLM 4.7 only
51
Like-for-like categories
7 of 9

Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.

Which one for your work

Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.

At a glance

Coding index
DeepSeek V4 Flash 0731 51.8 from 4 benchmarks, GLM 4.7 55.1 from 2 benchmarks.
Widest category
Math, 30.6 points apart on average over 2 shared benchmarks.
Widest single gap
ProofBench: DeepSeek V4 Flash 0731 56.0% against GLM 4.7 6.0%, 50.0 points apart on a 0 to 100 scale.
Output price
DeepSeek V4 Flash 0731 $0.28 against GLM 4.7 $2.20 per million output tokens, 7.9x apart.
Context window
DeepSeek V4 Flash 0731 takes 1.05M tokens, GLM 4.7 205K.

Benchmark by benchmark

First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.

Boards won, where both have a result
CategoryDeepSeek V4 Flash 0731BarsGLM 4.7Ties
Coding40
Intelligence20
Reasoning60
Math20
Knowledge51
Web design62
General20
All shared boards273
CodingLike-for-likeSix of these boards feed the Vibe Coding Index40
Coding benchmarks for DeepSeek V4 Flash 0731 and GLM 4.7
BenchmarkDeepSeek V4 Flash 0731GLM 4.7Leader
LMArena WebDevNot measured1435Only GLM 4.7 measured
AA Coding Index69.145.3DeepSeek V4 Flash 0731
LiveCodeBench (Vals AI)87.3%82.2%DeepSeek V4 Flash 0731
SWE-bench Verified (Vals AI)88.8%69.4%DeepSeek V4 Flash 0731
Terminal-Bench 4 (Vals AI)18.7%Not measuredOnly DeepSeek V4 Flash 0731 measured
Vibe Code Bench (Vals AI)74.7%Not measuredOnly DeepSeek V4 Flash 0731 measured
Code migration (Vals AI)38.6%Not measuredOnly DeepSeek V4 Flash 0731 measured
ProgramBench (Vals AI)0.0%Not measuredOnly DeepSeek V4 Flash 0731 measured
IOI (Vals AI)32.7%Not measuredOnly DeepSeek V4 Flash 0731 measured
Terminal-Bench 2.1 (Vals AI)67.0%Not measuredOnly DeepSeek V4 Flash 0731 measured
SkillsBench (Vals AI)50.7%Not measuredOnly DeepSeek V4 Flash 0731 measured
CyberBench (Vals AI)72.1%Not measuredOnly DeepSeek V4 Flash 0731 measured
LiveCodeBench (Artificial Analysis run)Not measured89.4%Only GLM 4.7 measured
SciCode50.3%Not measuredOnly DeepSeek V4 Flash 0731 measured
Terminal-Bench Hard (Artificial Analysis run)Not measured31.8%Only GLM 4.7 measured
Terminal-BenchNot measured33.4%Only GLM 4.7 measured
FrontierCode18.8%Not measuredOnly DeepSeek V4 Flash 0731 measured
WeirdML63.0%Not measuredOnly DeepSeek V4 Flash 0731 measured
ALE-Bench1306.1399.5DeepSeek V4 Flash 0731
LMArena Text: codingNot measured1454Only GLM 4.7 measured
LMArena Text: software and ITNot measured1453Only GLM 4.7 measured
LMArena WebDev: ReactNot measured1420Only GLM 4.7 measured
LMArena WebDev: HTMLNot measured1447Only GLM 4.7 measured
Neither model has a result on the other 16 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for DeepSeek V4 Flash 0731 and GLM 4.7
BenchmarkDeepSeek V4 Flash 0731GLM 4.7Leader
AA Intelligence Index34.322.2DeepSeek V4 Flash 0731
Epoch Capabilities Index154.8143.6DeepSeek V4 Flash 0731
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index14 boards, none shared
Agentic work benchmarks for DeepSeek V4 Flash 0731 and GLM 4.7
BenchmarkDeepSeek V4 Flash 0731GLM 4.7Leader
AA Agentic Index41.0Not measuredOnly DeepSeek V4 Flash 0731 measured
Design Arena: agents building full-stack appsNot measured1050Only GLM 4.7 measured
Design Arena: agents building mobile appsNot measured1105Only GLM 4.7 measured
Design Arena: agents building Android appsNot measured1112Only GLM 4.7 measured
Design Arena: agents building Godot gamesNot measured1058Only GLM 4.7 measured
Finance Agent (Vals AI)49.5%Not measuredOnly DeepSeek V4 Flash 0731 measured
Tax Agent Bench (Vals AI)28.1%Not measuredOnly DeepSeek V4 Flash 0731 measured
Legal Research Bench (Vals AI)30.3%Not measuredOnly DeepSeek V4 Flash 0731 measured
Excel Modeling Benchmark (Vals AI)57.0%Not measuredOnly DeepSeek V4 Flash 0731 measured
BioMysteryBench (Vals AI)64.4%Not measuredOnly DeepSeek V4 Flash 0731 measured
Terminal-Bench-Science (Vals AI)4.3%Not measuredOnly DeepSeek V4 Flash 0731 measured
τ²-Bench TelecomNot measured95.9%Only GLM 4.7 measured
Vending-Bench 2Not measured$2,377Only GLM 4.7 measured
BrowseComp-PlusNot measured64.7%Only GLM 4.7 measured
Neither model has a result on the other 27 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index60
Reasoning benchmarks for DeepSeek V4 Flash 0731 and GLM 4.7
BenchmarkDeepSeek V4 Flash 0731GLM 4.7Leader
GPQA Diamond89.9%80.0%DeepSeek V4 Flash 0731
GPQA Diamond (Artificial Analysis run)90.8%85.9%DeepSeek V4 Flash 0731
Humanity's Last Exam (Artificial Analysis run)38.6%27.4%DeepSeek V4 Flash 0731
GPQA Diamond (Epoch AI run)91.0%83.3%DeepSeek V4 Flash 0731
ARC-AGI89.0%Not measuredOnly DeepSeek V4 Flash 0731 measured
ARC-AGI-261.4%Not measuredOnly DeepSeek V4 Flash 0731 measured
SimpleBench61.1%47.7%DeepSeek V4 Flash 0731
Chess puzzles32.0%21.0%DeepSeek V4 Flash 0731
Mystery game puzzles34.0%Not measuredOnly DeepSeek V4 Flash 0731 measured
LMArena Text: hard promptsNot measured1443Only GLM 4.7 measured
LMArena Text: expertNot measured1424Only GLM 4.7 measured
LMArena Text: hard prompts in EnglishNot measured1452Only GLM 4.7 measured
Neither model has a result on the other 10 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index20
Math benchmarks for DeepSeek V4 Flash 0731 and GLM 4.7
BenchmarkDeepSeek V4 Flash 0731GLM 4.7Leader
AIMENot measured93.3%Only GLM 4.7 measured
MGSM (Vals AI)Not measured88.2%Only GLM 4.7 measured
AA Math IndexNot measured95.0Only GLM 4.7 measured
AIME 2025 (Artificial Analysis run)Not measured95.0%Only GLM 4.7 measured
OTIS Mock AIME94.4%83.3%DeepSeek V4 Flash 0731
FrontierMath, tiers 1 to 357.5%Not measuredOnly DeepSeek V4 Flash 0731 measured
FrontierMath, tier 424.4%Not measuredOnly DeepSeek V4 Flash 0731 measured
ProofBench56.0%6.0%DeepSeek V4 Flash 0731
LMArena Text: mathNot measured1424Only GLM 4.7 measured
LMArena Text: mathematical workNot measured1411Only GLM 4.7 measured
Neither model has a result on the other 3 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index51
Knowledge benchmarks for DeepSeek V4 Flash 0731 and GLM 4.7
BenchmarkDeepSeek V4 Flash 0731GLM 4.7Leader
MMLU Pro86.2%82.7%DeepSeek V4 Flash 0731
LegalBench (Vals AI)77.7%83.4%GLM 4.7
CaseLaw (Vals AI)Not measured54.9%Only GLM 4.7 measured
CorpFin (Vals AI)61.9%46.4%DeepSeek V4 Flash 0731
TaxEval (Vals AI)70.7%68.8%DeepSeek V4 Flash 0731
MedQA (Vals AI)Not measured93.7%Only GLM 4.7 measured
MedCode (Vals AI)41.4%32.8%DeepSeek V4 Flash 0731
MMLU Pro (Artificial Analysis run)Not measured85.6%Only GLM 4.7 measured
SimpleQA Verified33.6%32.2%DeepSeek V4 Flash 0731
LMArena Text: scienceNot measured1457Only GLM 4.7 measured
LMArena Text: medicine and healthcareNot measured1469Only GLM 4.7 measured
LMArena Text: legal and governmentNot measured1444Only GLM 4.7 measured
LMArena Text: business and financeNot measured1429Only GLM 4.7 measured
Neither model has a result on the other 5 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index62
Web design benchmarks for DeepSeek V4 Flash 0731 and GLM 4.7
BenchmarkDeepSeek V4 Flash 0731GLM 4.7Leader
Design Arena: websites12381226DeepSeek V4 Flash 0731
Design Arena: UI components12351199DeepSeek V4 Flash 0731
Design Arena: game dev12081189DeepSeek V4 Flash 0731
Design Arena: data viz11801195GLM 4.7
Design Arena: 3D12091191DeepSeek V4 Flash 0731
Design Arena: all code categories12301217DeepSeek V4 Flash 0731
Design Arena: SVG11851143DeepSeek V4 Flash 0731
Design Arena: ASCII art10901165GLM 4.7
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index20
General benchmarks for DeepSeek V4 Flash 0731 and GLM 4.7
BenchmarkDeepSeek V4 Flash 0731GLM 4.7Leader
MedScribe (Vals AI)80.4%68.6%DeepSeek V4 Flash 0731
IFBenchNot measured67.9%Only GLM 4.7 measured
Long context reasoning (AA-LCR)79.7%71.0%DeepSeek V4 Flash 0731
DTBench90.9%Not measuredOnly DeepSeek V4 Flash 0731 measured
LMCA41.7%Not measuredOnly DeepSeek V4 Flash 0731 measured
CL-benchNot measured15.9%Only GLM 4.7 measured
CL-bench LifeNot measured10.9%Only GLM 4.7 measured
LMArena TextNot measured1435Only GLM 4.7 measured
LMArena Text: instruction followingNot measured1412Only GLM 4.7 measured
LMArena Text: creative writingNot measured1401Only GLM 4.7 measured
LMArena Text: EnglishNot measured1453Only GLM 4.7 measured
LMArena Text: non-EnglishNot measured1417Only GLM 4.7 measured
LMArena Text: ChineseNot measured1495Only GLM 4.7 measured
LMArena Text: GermanNot measured1426Only GLM 4.7 measured
LMArena Text: JapaneseNot measured1439Only GLM 4.7 measured
LMArena Text: KoreanNot measured1399Only GLM 4.7 measured
LMArena Text: FrenchNot measured1432Only GLM 4.7 measured
LMArena Text: SpanishNot measured1434Only GLM 4.7 measured
LMArena Text: RussianNot measured1423Only GLM 4.7 measured
LMArena Text: PolishNot measured1435Only GLM 4.7 measured
LMArena Text: multi-turnNot measured1446Only GLM 4.7 measured
LMArena Text: longer queriesNot measured1432Only GLM 4.7 measured
LMArena Text: writing and languageNot measured1411Only GLM 4.7 measured
LMArena Text: entertainment and mediaNot measured1400Only GLM 4.7 measured
Neither model has a result on the other 22 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for DeepSeek V4 Flash 0731 and GLM 4.7
BenchmarkDeepSeek V4 Flash 0731GLM 4.7Leader
Neither model has a result on 5 boards here

What each workload costs

Three fixed token mixes at each model's listed price, so per-token rates become a bill.

Chat turn

1K input + 500 output tokens

DeepSeek V4 Flash 0731$0.0003Fits in one request
GLM 4.7$0.0017Fits in one request

DeepSeek V4 Flash 0731 costs less

Repository review

50K input + 3K output tokens

DeepSeek V4 Flash 0731$0.0078Fits in one request
GLM 4.7$0.037Fits in one request

DeepSeek V4 Flash 0731 costs less

Agent loop

200K input + 10K output tokens

DeepSeek V4 Flash 0731$0.031Fits in one request
GLM 4.7$0.142Exceeds the context window

DeepSeek V4 Flash 0731 costs less

Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.

Specification differences

The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.

Specifications of DeepSeek V4 Flash 0731 and GLM 4.7
SpecificationDeepSeek V4 Flash 0731Z.ai GLM 4.7
MakerDeepSeekZ.ai
WeightsOpen weightsOpen weights
ReleasedJuly 31, 2026December 22, 2025
Context window1.05M205K
Input $/Mtok$0.14$0.60
Output $/Mtok$0.28$2.20
Coding index51.855.1
Independent measurements behind it42
Cost per solved task$0.01$0.29
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V4 Flash 0731 better than GLM 4.7 for coding?

Pick GLM 4.7 for coding: it scores 55.1 on the Vibe Coding Index against 51.8 for DeepSeek V4 Flash 0731, though on 2 benchmarks against 4. Pick DeepSeek V4 Flash 0731 for output tokens 7.9x cheaper ($0.28 vs $2.20 per million) and a lower cost per solved task ($0.01 against $0.29).

Which is cheaper, DeepSeek V4 Flash 0731 or GLM 4.7?

DeepSeek V4 Flash 0731 costs $0.14 per million input tokens and $0.28 per million output tokens; GLM 4.7 costs $0.60 and $2.20. Per solved SWE-bench Verified task, DeepSeek V4 Flash 0731 costs $0.01 and GLM 4.7 $0.29.

Which has the bigger context window, DeepSeek V4 Flash 0731 or GLM 4.7?

DeepSeek V4 Flash 0731, with 1.05M tokens against 205K.

How many benchmarks is the DeepSeek V4 Flash 0731 vs GLM 4.7 comparison based on?

30 benchmarks have a result for both models as of October 21, 2026. DeepSeek V4 Flash 0731's coding index rests on 4 independent benchmarks and GLM 4.7's on 2. Where only one model has a result, the page says so instead of naming a winner.

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<p style="font:13px/1.4 sans-serif;margin:6px 0 0">Source: <a href="https://llmbenchmark.ai/compare/deepseek-v4-flash-0731-vs-glm-4-7">LLMBenchmark.ai, DeepSeek V4 Flash 0731 vs GLM 4.7</a></p>