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DeepSeek V3.2 vs GLM 4.7 Flash

DeepSeek V3.2 leads GLM 4.7 Flash on the Artificial Analysis Intelligence Index, 21.5 to 14.9, and GLM 4.7 Flash costs 2.2x less per output token ($0.40 vs $0.88 per million). Updated October 21, 2026; 41 benchmarks have a result for both.

Replace DeepSeek V3.2 Replace GLM 4.7 Flash
DeepSeek V3.2DeepSeek
Coding
30.0
Overall
37.9
Output $/M
$0.88
34
GLM 4.7 FlashZ.ai
Coding
No data
Overall
42.1
Output $/M
$0.40
7
vs boards won of 41 shared

DeepSeek V3.2 or GLM 4.7 Flash: which to pick

Only DeepSeek V3.2 has a coding score, 30.0 on the Vibe Coding Index; GLM 4.7 Flash has none, so the two cannot be ranked on coding.

Pick GLM 4.7 Flash for output tokens 2.2x cheaper ($0.40 vs $0.88 per million) and a larger context window (200K against 164K tokens).

Model ADeepSeek V3.2DeepSeek30.0/1003 independent benchmarks$0.99 per solved taskModel BGLM 4.7 FlashZ.aiNot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
41
DeepSeek V3.2 only
34
GLM 4.7 Flash only
2
Like-for-like categories
8 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 V3.2 30.0 from 3 benchmarks, GLM 4.7 Flash not benchmarked.
Widest category
Reasoning, 16.4 points apart on average over 5 shared benchmarks.
Widest single gap
Long context reasoning (AA-LCR): DeepSeek V3.2 73.3% against GLM 4.7 Flash 41.7%, 31.7 points apart on a 0 to 100 scale.
Output price
DeepSeek V3.2 $0.88 against GLM 4.7 Flash $0.40 per million output tokens, 2.2x apart.
Context window
DeepSeek V3.2 takes 164K tokens, GLM 4.7 Flash 200K.

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 V3.2BarsGLM 4.7 FlashTies
Coding30
Intelligence10
Agentic work01
Reasoning50
Math20
Knowledge40
Web design25
General171
All shared boards347
CodingLike-for-likeSix of these boards feed the Vibe Coding Index30
Coding benchmarks for DeepSeek V3.2 and GLM 4.7 Flash
BenchmarkDeepSeek V3.2GLM 4.7 FlashLeader
SWE-bench Verified70.0%Not measuredOnly DeepSeek V3.2 measured
SWE-bench Multilingual59.0%Not measuredOnly DeepSeek V3.2 measured
LMArena WebDev1362Not measuredOnly DeepSeek V3.2 measured
AA Coding Index44.2Not measuredOnly DeepSeek V3.2 measured
LiveCodeBench (Vals AI)80.7%Not measuredOnly DeepSeek V3.2 measured
SWE-bench Verified (Vals AI)67.6%Not measuredOnly DeepSeek V3.2 measured
Vibe Code Bench (Vals AI)5.1%Not measuredOnly DeepSeek V3.2 measured
LiveCodeBench (Artificial Analysis run)86.2%Not measuredOnly DeepSeek V3.2 measured
Terminal-Bench Hard (Artificial Analysis run)35.6%22.0%DeepSeek V3.2
Terminal-Bench39.6%Not measuredOnly DeepSeek V3.2 measured
LMArena Text: coding14531382DeepSeek V3.2
LMArena Text: software and IT14491389DeepSeek V3.2
LMArena WebDev: React1350Not measuredOnly DeepSeek V3.2 measured
LMArena WebDev: HTML1371Not measuredOnly DeepSeek V3.2 measured
Neither model has a result on the other 25 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for DeepSeek V3.2 and GLM 4.7 Flash
BenchmarkDeepSeek V3.2GLM 4.7 FlashLeader
AA Intelligence Index21.514.9DeepSeek V3.2
Epoch Capabilities Index146.1Not measuredOnly DeepSeek V3.2 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for DeepSeek V3.2 and GLM 4.7 Flash
BenchmarkDeepSeek V3.2GLM 4.7 FlashLeader
τ²-Bench Telecom90.6%98.8%GLM 4.7 Flash
APEX-Agents21.3%Not measuredOnly DeepSeek V3.2 measured
Vending-Bench 2$1,034Not measuredOnly DeepSeek V3.2 measured
Neither model has a result on the other 38 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index50
Reasoning benchmarks for DeepSeek V3.2 and GLM 4.7 Flash
BenchmarkDeepSeek V3.2GLM 4.7 FlashLeader
GPQA Diamond80.3%Not measuredOnly DeepSeek V3.2 measured
GPQA Diamond (Artificial Analysis run)84.0%58.1%DeepSeek V3.2
Humanity's Last Exam (Artificial Analysis run)24.6%7.6%DeepSeek V3.2
GPQA Diamond (Epoch AI run)Not measured60.5%Only GLM 4.7 Flash measured
ARC-AGI57.0%Not measuredOnly DeepSeek V3.2 measured
ARC-AGI-24.0%Not measuredOnly DeepSeek V3.2 measured
LMArena Text: hard prompts14341356DeepSeek V3.2
LMArena Text: expert14361357DeepSeek V3.2
LMArena Text: hard prompts in English14461369DeepSeek V3.2
Neither model has a result on the other 13 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index20
Math benchmarks for DeepSeek V3.2 and GLM 4.7 Flash
BenchmarkDeepSeek V3.2GLM 4.7 FlashLeader
AIME84.6%Not measuredOnly DeepSeek V3.2 measured
MGSM (Vals AI)86.0%Not measuredOnly DeepSeek V3.2 measured
AA Math Index92.0Not measuredOnly DeepSeek V3.2 measured
AIME 2025 (Artificial Analysis run)92.0%Not measuredOnly DeepSeek V3.2 measured
OTIS Mock AIMENot measured58.3%Only GLM 4.7 Flash measured
LMArena Text: math14351355DeepSeek V3.2
LMArena Text: mathematical work14401369DeepSeek V3.2
Neither model has a result on the other 6 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
Knowledge benchmarks for DeepSeek V3.2 and GLM 4.7 Flash
BenchmarkDeepSeek V3.2GLM 4.7 FlashLeader
MMLU Pro84.9%Not measuredOnly DeepSeek V3.2 measured
LegalBench (Vals AI)76.1%Not measuredOnly DeepSeek V3.2 measured
CaseLaw (Vals AI)55.4%Not measuredOnly DeepSeek V3.2 measured
CorpFin (Vals AI)51.0%Not measuredOnly DeepSeek V3.2 measured
TaxEval (Vals AI)68.2%Not measuredOnly DeepSeek V3.2 measured
MedQA (Vals AI)93.9%Not measuredOnly DeepSeek V3.2 measured
MMLU Pro (Artificial Analysis run)86.2%Not measuredOnly DeepSeek V3.2 measured
LMArena Text: science14461358DeepSeek V3.2
LMArena Text: medicine and healthcare14401343DeepSeek V3.2
LMArena Text: legal and government14251357DeepSeek V3.2
LMArena Text: business and finance14101343DeepSeek V3.2
Neither model has a result on the other 7 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index25
Web design benchmarks for DeepSeek V3.2 and GLM 4.7 Flash
BenchmarkDeepSeek V3.2GLM 4.7 FlashLeader
Design Arena: websites11751194GLM 4.7 Flash
Design Arena: UI components11491208GLM 4.7 Flash
Design Arena: game dev11321135GLM 4.7 Flash
Design Arena: data viz11581123DeepSeek V3.2
Design Arena: 3D11331121DeepSeek V3.2
Design Arena: all code categories11641178GLM 4.7 Flash
Design Arena: SVG10321038GLM 4.7 Flash
Design Arena: ASCII art1083Not measuredOnly DeepSeek V3.2 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index171
General benchmarks for DeepSeek V3.2 and GLM 4.7 Flash
BenchmarkDeepSeek V3.2GLM 4.7 FlashLeader
IFBench60.7%60.8%GLM 4.7 Flash
Long context reasoning (AA-LCR)73.3%41.7%DeepSeek V3.2
DTBench85.6%Not measuredOnly DeepSeek V3.2 measured
LMCA28.8%Not measuredOnly DeepSeek V3.2 measured
CL-bench12.4%Not measuredOnly DeepSeek V3.2 measured
CL-bench Life7.4%Not measuredOnly DeepSeek V3.2 measured
LMArena Text14251351DeepSeek V3.2
LMArena Text: instruction following14131327DeepSeek V3.2
LMArena Text: creative writing14001296DeepSeek V3.2
LMArena Text: English14391373DeepSeek V3.2
LMArena Text: non-English14091330DeepSeek V3.2
LMArena Text: Chinese14551403DeepSeek V3.2
LMArena Text: German14131336DeepSeek V3.2
LMArena Text: Japanese1374Not measuredOnly DeepSeek V3.2 measured
LMArena Text: Korean13701283DeepSeek V3.2
LMArena Text: French14291332DeepSeek V3.2
LMArena Text: Spanish14241350DeepSeek V3.2
LMArena Text: Russian14241333DeepSeek V3.2
LMArena Text: Polish14191291DeepSeek V3.2
LMArena Text: multi-turn14271342DeepSeek V3.2
LMArena Text: longer queries14281345DeepSeek V3.2
LMArena Text: writing and language14071320DeepSeek V3.2
LMArena Text: entertainment and media13951304DeepSeek V3.2
Neither model has a result on the other 23 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for DeepSeek V3.2 and GLM 4.7 Flash
BenchmarkDeepSeek V3.2GLM 4.7 FlashLeader
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 V3.2$0.0007Fits in one request
GLM 4.7 Flash$0.0003Fits in one request

GLM 4.7 Flash costs less

Repository review

50K input + 3K output tokens

DeepSeek V3.2$0.017Fits in one request
GLM 4.7 Flash$0.0045Fits in one request

GLM 4.7 Flash costs less

Agent loop

200K input + 10K output tokens

DeepSeek V3.2$0.067Exceeds the context window
GLM 4.7 Flash$0.017Exceeds the context window

GLM 4.7 Flash 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 V3.2 and GLM 4.7 Flash
SpecificationDeepSeek V3.2Z.ai GLM 4.7 Flash
MakerDeepSeekZ.ai
WeightsOpen weightsOpen weights
ReleasedDecember 1, 2025January 19, 2026
Context window164K200K
Input $/Mtok$0.29$0.0653
Output $/Mtok$0.88$0.40
Coding index30.0Not benchmarked
Independent measurements behind it30
Cost per solved task$0.99Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V3.2 better than GLM 4.7 Flash for coding?

Only DeepSeek V3.2 has a coding score, 30.0 on the Vibe Coding Index; GLM 4.7 Flash has none, so the two cannot be ranked on coding. Pick GLM 4.7 Flash for output tokens 2.2x cheaper ($0.40 vs $0.88 per million) and a larger context window (200K against 164K tokens).

Which is cheaper, DeepSeek V3.2 or GLM 4.7 Flash?

DeepSeek V3.2 costs $0.29 per million input tokens and $0.88 per million output tokens; GLM 4.7 Flash costs $0.0653 and $0.40. Cost per solved task is known for DeepSeek V3.2 only.

Which has the bigger context window, DeepSeek V3.2 or GLM 4.7 Flash?

GLM 4.7 Flash, with 200K tokens against 164K.

How many benchmarks is the DeepSeek V3.2 vs GLM 4.7 Flash comparison based on?

41 benchmarks have a result for both models as of October 21, 2026. DeepSeek V3.2's coding index rests on 3 independent benchmarks and GLM 4.7 Flash's on 0. Where only one model has a result, the page says so instead of naming a winner.

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