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DeepSeek V4 Pro 0813 vs GLM 4.7

DeepSeek V4 Pro 0813 leads GLM 4.7 on coding, 56.1 to 55.1 on the Vibe Coding Index, at about the same output price ($1.98 vs $2.20 per million). Updated October 21, 2026; 49 benchmarks have a result for both.

Replace DeepSeek V4 Pro 0813 Replace GLM 4.7
DeepSeek V4 Pro 0813DeepSeek
Coding
56.1
Overall
60.8
Output $/M
$1.98
45
GLM 4.7Z.ai
Coding
55.1
Overall
56.9
Output $/M
$2.20
4
vs boards won of 49 shared

DeepSeek V4 Pro 0813 or GLM 4.7: which to pick

DeepSeek V4 Pro 0813 and GLM 4.7 are level for coding, 56.1 against 55.1 on the Vibe Coding Index, so price and context decide.

Pick GLM 4.7 for work measured by LegalBench (Vals AI) or LMArena Text: science, where it leads. Pick DeepSeek V4 Pro 0813 for output tokens 1.1x cheaper ($1.98 vs $2.20 per million) and a lower cost per solved task ($0.10 against $0.29).

Model ADeepSeek V4 Pro 0813DeepSeek56.1/1005 independent benchmarks$0.10 per solved taskModel BGLM 4.7Z.ai55.1/1002 independent benchmarks$0.29 per solved task
Shared results
49
DeepSeek V4 Pro 0813 only
29
GLM 4.7 only
32
Like-for-like categories
6 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 Pro 0813 56.1 from 5 benchmarks, GLM 4.7 55.1 from 2 benchmarks.
Widest category
Coding, 18.0 points apart on average over 9 shared benchmarks.
Widest single gap
ProofBench: DeepSeek V4 Pro 0813 50.0% against GLM 4.7 6.0%, 44.0 points apart on a 0 to 100 scale.
Output price
DeepSeek V4 Pro 0813 $1.98 against GLM 4.7 $2.20 per million output tokens, 1.1x apart.
Context window
DeepSeek V4 Pro 0813 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 Pro 0813BarsGLM 4.7Ties
Coding90
Intelligence20
Reasoning80
Math40
Knowledge73
General151
All shared boards454
CodingLike-for-likeSix of these boards feed the Vibe Coding Index90
Coding benchmarks for DeepSeek V4 Pro 0813 and GLM 4.7
BenchmarkDeepSeek V4 Pro 0813GLM 4.7Leader
LMArena WebDev15821435DeepSeek V4 Pro 0813
AA Coding Index68.845.3DeepSeek V4 Pro 0813
LiveCodeBench (Vals AI)87.5%82.2%DeepSeek V4 Pro 0813
SWE-bench Verified (Vals AI)96.4%69.4%DeepSeek V4 Pro 0813
Terminal-Bench 4 (Vals AI)14.1%Not measuredOnly DeepSeek V4 Pro 0813 measured
Vibe Code Bench (Vals AI)82.3%Not measuredOnly DeepSeek V4 Pro 0813 measured
Code migration (Vals AI)41.5%Not measuredOnly DeepSeek V4 Pro 0813 measured
ProgramBench (Vals AI)0.0%Not measuredOnly DeepSeek V4 Pro 0813 measured
IOI (Vals AI)51.6%Not measuredOnly DeepSeek V4 Pro 0813 measured
Terminal-Bench 2.1 (Vals AI)54.7%Not measuredOnly DeepSeek V4 Pro 0813 measured
Vibe Code Bench 1-100 (Vals AI)17.5%Not measuredOnly DeepSeek V4 Pro 0813 measured
SkillsBench (Vals AI)53.8%Not measuredOnly DeepSeek V4 Pro 0813 measured
CyberBench (Vals AI)72.9%Not measuredOnly DeepSeek V4 Pro 0813 measured
LiveCodeBench (Artificial Analysis run)Not measured89.4%Only GLM 4.7 measured
SciCode51.0%Not measuredOnly DeepSeek V4 Pro 0813 measured
Terminal-Bench Hard (Artificial Analysis run)Not measured31.8%Only GLM 4.7 measured
Terminal-BenchNot measured33.4%Only GLM 4.7 measured
FrontierCode28.5%Not measuredOnly DeepSeek V4 Pro 0813 measured
WeirdML66.2%Not measuredOnly DeepSeek V4 Pro 0813 measured
ALE-Bench1403.2399.5DeepSeek V4 Pro 0813
LMArena Text: coding14691454DeepSeek V4 Pro 0813
LMArena Text: software and IT14621453DeepSeek V4 Pro 0813
LMArena WebDev: React15881420DeepSeek V4 Pro 0813
LMArena WebDev: HTML15661447DeepSeek V4 Pro 0813
Neither model has a result on the other 15 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for DeepSeek V4 Pro 0813 and GLM 4.7
BenchmarkDeepSeek V4 Pro 0813GLM 4.7Leader
AA Intelligence Index36.022.2DeepSeek V4 Pro 0813
Epoch Capabilities Index155.6143.6DeepSeek V4 Pro 0813
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index16 boards, none shared
Agentic work benchmarks for DeepSeek V4 Pro 0813 and GLM 4.7
BenchmarkDeepSeek V4 Pro 0813GLM 4.7Leader
AA Agentic Index41.3Not measuredOnly DeepSeek V4 Pro 0813 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
SREBench (Vals AI)1.9%Not measuredOnly DeepSeek V4 Pro 0813 measured
Finance Agent (Vals AI)50.4%Not measuredOnly DeepSeek V4 Pro 0813 measured
Tax Agent Bench (Vals AI)26.8%Not measuredOnly DeepSeek V4 Pro 0813 measured
Legal Research Bench (Vals AI)40.9%Not measuredOnly DeepSeek V4 Pro 0813 measured
Harvey's Legal Agent Benchmark (Vals AI)10.8%Not measuredOnly DeepSeek V4 Pro 0813 measured
Excel Modeling Benchmark (Vals AI)52.8%Not measuredOnly DeepSeek V4 Pro 0813 measured
Terminal-Bench-Science (Vals AI)4.3%Not measuredOnly DeepSeek V4 Pro 0813 measured
τ²-Bench TelecomNot measured95.9%Only GLM 4.7 measured
APEX-Agents47.3%Not measuredOnly DeepSeek V4 Pro 0813 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 25 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index80
Reasoning benchmarks for DeepSeek V4 Pro 0813 and GLM 4.7
BenchmarkDeepSeek V4 Pro 0813GLM 4.7Leader
GPQA Diamond92.4%80.0%DeepSeek V4 Pro 0813
GPQA Diamond (Artificial Analysis run)92.8%85.9%DeepSeek V4 Pro 0813
Humanity's Last Exam (Artificial Analysis run)41.0%27.4%DeepSeek V4 Pro 0813
GPQA Diamond (Epoch AI run)91.7%83.3%DeepSeek V4 Pro 0813
ARC-AGI90.5%Not measuredOnly DeepSeek V4 Pro 0813 measured
ARC-AGI-261.3%Not measuredOnly DeepSeek V4 Pro 0813 measured
SimpleBenchNot measured47.7%Only GLM 4.7 measured
Chess puzzles46.0%21.0%DeepSeek V4 Pro 0813
Mystery game puzzles43.0%Not measuredOnly DeepSeek V4 Pro 0813 measured
LMArena Text: hard prompts14581443DeepSeek V4 Pro 0813
LMArena Text: expert14591424DeepSeek V4 Pro 0813
LMArena Text: hard prompts in English14631452DeepSeek V4 Pro 0813
Neither model has a result on the other 10 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index40
Math benchmarks for DeepSeek V4 Pro 0813 and GLM 4.7
BenchmarkDeepSeek V4 Pro 0813GLM 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 AIME98.6%83.3%DeepSeek V4 Pro 0813
FrontierMath, tiers 1 to 364.6%Not measuredOnly DeepSeek V4 Pro 0813 measured
FrontierMath, tier 426.8%Not measuredOnly DeepSeek V4 Pro 0813 measured
ProofBench50.0%6.0%DeepSeek V4 Pro 0813
LMArena Text: math14411424DeepSeek V4 Pro 0813
LMArena Text: mathematical work14431411DeepSeek V4 Pro 0813
Neither model has a result on the other 3 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index73
Knowledge benchmarks for DeepSeek V4 Pro 0813 and GLM 4.7
BenchmarkDeepSeek V4 Pro 0813GLM 4.7Leader
MMLU Pro87.0%82.7%DeepSeek V4 Pro 0813
LegalBench (Vals AI)82.4%83.4%GLM 4.7
CaseLaw (Vals AI)Not measured54.9%Only GLM 4.7 measured
CorpFin (Vals AI)65.4%46.4%DeepSeek V4 Pro 0813
TaxEval (Vals AI)73.1%68.8%DeepSeek V4 Pro 0813
MedQA (Vals AI)Not measured93.7%Only GLM 4.7 measured
MedCode (Vals AI)42.5%32.8%DeepSeek V4 Pro 0813
MMLU Pro (Artificial Analysis run)Not measured85.6%Only GLM 4.7 measured
SimpleQA Verified52.9%32.2%DeepSeek V4 Pro 0813
LMArena Text: science14571457GLM 4.7
LMArena Text: medicine and healthcare14461469GLM 4.7
LMArena Text: legal and government14591444DeepSeek V4 Pro 0813
LMArena Text: business and finance14421429DeepSeek V4 Pro 0813
Neither model has a result on the other 5 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Web design benchmarks for DeepSeek V4 Pro 0813 and GLM 4.7
BenchmarkDeepSeek V4 Pro 0813GLM 4.7Leader
Design Arena: websitesNot measured1226Only GLM 4.7 measured
Design Arena: UI componentsNot measured1199Only GLM 4.7 measured
Design Arena: game devNot measured1189Only GLM 4.7 measured
Design Arena: data vizNot measured1195Only GLM 4.7 measured
Design Arena: 3DNot measured1191Only GLM 4.7 measured
Design Arena: all code categoriesNot measured1217Only GLM 4.7 measured
Design Arena: SVGNot measured1143Only GLM 4.7 measured
Design Arena: ASCII artNot measured1165Only GLM 4.7 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index151
General benchmarks for DeepSeek V4 Pro 0813 and GLM 4.7
BenchmarkDeepSeek V4 Pro 0813GLM 4.7Leader
Vals Index53.0%Not measuredOnly DeepSeek V4 Pro 0813 measured
MedScribe (Vals AI)80.2%68.6%DeepSeek V4 Pro 0813
IFBenchNot measured67.9%Only GLM 4.7 measured
Long context reasoning (AA-LCR)80.3%71.0%DeepSeek V4 Pro 0813
DTBench93.9%Not measuredOnly DeepSeek V4 Pro 0813 measured
LMCA45.5%Not measuredOnly DeepSeek V4 Pro 0813 measured
CL-benchNot measured15.9%Only GLM 4.7 measured
CL-bench LifeNot measured10.9%Only GLM 4.7 measured
LMArena Text14461435DeepSeek V4 Pro 0813
LMArena Text: instruction following14481412DeepSeek V4 Pro 0813
LMArena Text: creative writing14391401DeepSeek V4 Pro 0813
LMArena Text: English14571453DeepSeek V4 Pro 0813
LMArena Text: non-English14311417DeepSeek V4 Pro 0813
LMArena Text: Chinese14811495GLM 4.7
LMArena Text: GermanNot measured1426Only GLM 4.7 measured
LMArena Text: JapaneseNot measured1439Only GLM 4.7 measured
LMArena Text: Korean14491399DeepSeek V4 Pro 0813
LMArena Text: French14461432DeepSeek V4 Pro 0813
LMArena Text: Spanish14351434DeepSeek V4 Pro 0813
LMArena Text: Russian14481423DeepSeek V4 Pro 0813
LMArena Text: PolishNot measured1435Only GLM 4.7 measured
LMArena Text: multi-turn14541446DeepSeek V4 Pro 0813
LMArena Text: longer queries14581432DeepSeek V4 Pro 0813
LMArena Text: writing and language14431411DeepSeek V4 Pro 0813
LMArena Text: entertainment and media14241400DeepSeek V4 Pro 0813
Neither model has a result on the other 21 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for DeepSeek V4 Pro 0813 and GLM 4.7
BenchmarkDeepSeek V4 Pro 0813GLM 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 Pro 0813$0.0016Fits in one request
GLM 4.7$0.0017Fits in one request

DeepSeek V4 Pro 0813 costs less

Repository review

50K input + 3K output tokens

DeepSeek V4 Pro 0813$0.039Fits in one request
GLM 4.7$0.037Fits in one request

GLM 4.7 costs less

Agent loop

200K input + 10K output tokens

DeepSeek V4 Pro 0813$0.152Fits in one request
GLM 4.7$0.142Exceeds the context window

GLM 4.7 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 Pro 0813 and GLM 4.7
SpecificationDeepSeek V4 Pro 0813Z.ai GLM 4.7
MakerDeepSeekZ.ai
WeightsOpen weightsOpen weights
ReleasedAugust 12, 2026December 22, 2025
Context window1.05M205K
Input $/Mtok$0.66$0.60
Output $/Mtok$1.98$2.20
Coding index56.155.1
Independent measurements behind it52
Cost per solved task$0.10$0.29
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V4 Pro 0813 better than GLM 4.7 for coding?

DeepSeek V4 Pro 0813 and GLM 4.7 are level for coding, 56.1 against 55.1 on the Vibe Coding Index, so price and context decide. Pick GLM 4.7 for work measured by LegalBench (Vals AI) or LMArena Text: science, where it leads. Pick DeepSeek V4 Pro 0813 for output tokens 1.1x cheaper ($1.98 vs $2.20 per million) and a lower cost per solved task ($0.10 against $0.29).

Which is cheaper, DeepSeek V4 Pro 0813 or GLM 4.7?

DeepSeek V4 Pro 0813 costs $0.66 per million input tokens and $1.98 per million output tokens; GLM 4.7 costs $0.60 and $2.20. Per solved SWE-bench Verified task, DeepSeek V4 Pro 0813 costs $0.10 and GLM 4.7 $0.29.

Which has the bigger context window, DeepSeek V4 Pro 0813 or GLM 4.7?

DeepSeek V4 Pro 0813, with 1.05M tokens against 205K.

How many benchmarks is the DeepSeek V4 Pro 0813 vs GLM 4.7 comparison based on?

49 benchmarks have a result for both models as of October 21, 2026. DeepSeek V4 Pro 0813's coding index rests on 5 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-pro-0813-vs-glm-4-7">LLMBenchmark.ai, DeepSeek V4 Pro 0813 vs GLM 4.7</a></p>