Enter opens the highlighted result. Esc closes.

R1 0528 vs GLM 4.7 Flash

GLM 4.7 Flash leads R1 0528 on the Artificial Analysis Intelligence Index, 14.9 to 13.1, and GLM 4.7 Flash costs 5.5x less per output token ($0.40 vs $2.18 per million). Updated October 21, 2026; 43 benchmarks have a result for both.

Replace R1 0528 Replace GLM 4.7 Flash
R1 0528DeepSeek
Coding
No data
Overall
46.8
Output $/M
$2.18
34
GLM 4.7 FlashZ.ai
Coding
No data
Overall
42.1
Output $/M
$0.40
9
vs boards won of 43 shared

R1 0528 or GLM 4.7 Flash: which to pick

Neither model has a coding score yet, so the two cannot be ranked on coding.

Pick R1 0528 for work measured by Terminal-Bench Hard (Artificial Analysis run) or AA Intelligence Index, where it leads.

Model AR1 0528DeepSeekNot benchmarkedNo coding benchmarkNo cost per solved taskModel BGLM 4.7 FlashZ.aiNot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
43
R1 0528 only
17
GLM 4.7 Flash only
0
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
R1 0528 not benchmarked, GLM 4.7 Flash not benchmarked.
Widest category
Agentic work, 62.3 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: R1 0528 36.5% against GLM 4.7 Flash 98.8%, 62.3 points apart on a 0 to 100 scale.
Output price
R1 0528 $2.18 against GLM 4.7 Flash $0.40 per million output tokens, 5.5x apart.
Context window
R1 0528 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
CategoryR1 0528BarsGLM 4.7 FlashTies
Coding21
Intelligence01
Agentic work01
Reasoning60
Math30
Knowledge40
Web design25
General171
All shared boards349
CodingLike-for-likeSix of these boards feed the Vibe Coding Index21
Coding benchmarks for R1 0528 and GLM 4.7 Flash
BenchmarkR1 0528GLM 4.7 FlashLeader
Aider polyglot71.4%Not measuredOnly R1 0528 measured
LiveCodeBench (Artificial Analysis run)77.0%Not measuredOnly R1 0528 measured
Terminal-Bench Hard (Artificial Analysis run)15.9%22.0%GLM 4.7 Flash
WeirdML41.6%Not measuredOnly R1 0528 measured
ALE-Bench804.1Not measuredOnly R1 0528 measured
LMArena Text: coding14271382R1 0528
LMArena Text: software and IT14351389R1 0528
Neither model has a result on the other 32 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for R1 0528 and GLM 4.7 Flash
BenchmarkR1 0528GLM 4.7 FlashLeader
AA Intelligence Index13.114.9GLM 4.7 Flash
Neither model has a result on the other 1 board here
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for R1 0528 and GLM 4.7 Flash
BenchmarkR1 0528GLM 4.7 FlashLeader
τ²-Bench Telecom36.5%98.8%GLM 4.7 Flash
METR time horizons53.8%Not measuredOnly R1 0528 measured
DeepResearch Bench35.1%Not measuredOnly R1 0528 measured
BrowseComp-Plus16.4%Not measuredOnly R1 0528 measured
Neither model has a result on the other 37 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index60
Reasoning benchmarks for R1 0528 and GLM 4.7 Flash
BenchmarkR1 0528GLM 4.7 FlashLeader
GPQA Diamond (Artificial Analysis run)81.3%58.1%R1 0528
Humanity's Last Exam (Artificial Analysis run)15.8%7.6%R1 0528
GPQA Diamond (Epoch AI run)76.3%60.5%R1 0528
ARC-AGI21.2%Not measuredOnly R1 0528 measured
ARC-AGI-21.1%Not measuredOnly R1 0528 measured
SimpleBench40.8%Not measuredOnly R1 0528 measured
LMArena Text: hard prompts14151356R1 0528
LMArena Text: expert13941357R1 0528
LMArena Text: hard prompts in English14221369R1 0528
Neither model has a result on the other 13 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index30
Math benchmarks for R1 0528 and GLM 4.7 Flash
BenchmarkR1 0528GLM 4.7 FlashLeader
AA Math Index76.0Not measuredOnly R1 0528 measured
AIME 2025 (Artificial Analysis run)76.0%Not measuredOnly R1 0528 measured
OTIS Mock AIME66.4%58.3%R1 0528
MATH level 596.6%Not measuredOnly R1 0528 measured
LMArena Text: math14001355R1 0528
LMArena Text: mathematical work14151369R1 0528
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
Knowledge benchmarks for R1 0528 and GLM 4.7 Flash
BenchmarkR1 0528GLM 4.7 FlashLeader
MMLU Pro (Artificial Analysis run)84.9%Not measuredOnly R1 0528 measured
LMArena Text: science14301358R1 0528
LMArena Text: medicine and healthcare14451343R1 0528
LMArena Text: legal and government14191357R1 0528
LMArena Text: business and finance14021343R1 0528
Neither model has a result on the other 13 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index25
Web design benchmarks for R1 0528 and GLM 4.7 Flash
BenchmarkR1 0528GLM 4.7 FlashLeader
Design Arena: websites11491194GLM 4.7 Flash
Design Arena: UI components11031208GLM 4.7 Flash
Design Arena: game dev10971135GLM 4.7 Flash
Design Arena: data viz11821123R1 0528
Design Arena: 3D11111121GLM 4.7 Flash
Design Arena: all code categories11391178GLM 4.7 Flash
Design Arena: SVG10391038R1 0528
Neither model has a result on the other 2 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index171
General benchmarks for R1 0528 and GLM 4.7 Flash
BenchmarkR1 0528GLM 4.7 FlashLeader
IFBench39.6%60.8%GLM 4.7 Flash
Long context reasoning (AA-LCR)55.7%41.7%R1 0528
Fiction.LiveBench75.0%Not measuredOnly R1 0528 measured
Creative writing (Lech Mazur)81.9%Not measuredOnly R1 0528 measured
LMArena Text14281351R1 0528
LMArena Text: instruction following13821327R1 0528
LMArena Text: creative writing14051296R1 0528
LMArena Text: English14371373R1 0528
LMArena Text: non-English14121330R1 0528
LMArena Text: Chinese14421403R1 0528
LMArena Text: German14041336R1 0528
LMArena Text: Japanese1391Not measuredOnly R1 0528 measured
LMArena Text: Korean13601283R1 0528
LMArena Text: French14171332R1 0528
LMArena Text: Spanish14111350R1 0528
LMArena Text: Russian14231333R1 0528
LMArena Text: Polish14281291R1 0528
LMArena Text: multi-turn14051342R1 0528
LMArena Text: longer queries13911345R1 0528
LMArena Text: writing and language14021320R1 0528
LMArena Text: entertainment and media14001304R1 0528
Neither model has a result on the other 25 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for R1 0528 and GLM 4.7 Flash
BenchmarkR1 0528GLM 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

R1 0528$0.0016Fits 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

R1 0528$0.032Fits 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

R1 0528$0.122Exceeds 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 R1 0528 and GLM 4.7 Flash
SpecificationDeepSeek R1 0528Z.ai GLM 4.7 Flash
MakerDeepSeekZ.ai
WeightsOpen weightsOpen weights
ReleasedMay 28, 2025January 19, 2026
Context window164K200K
Input $/Mtok$0.50$0.0653
Output $/Mtok$2.18$0.40
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is R1 0528 better than GLM 4.7 Flash for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick R1 0528 for work measured by Terminal-Bench Hard (Artificial Analysis run) or AA Intelligence Index, where it leads.

Which is cheaper, R1 0528 or GLM 4.7 Flash?

R1 0528 costs $0.50 per million input tokens and $2.18 per million output tokens; GLM 4.7 Flash costs $0.0653 and $0.40. Cost per solved task is known for neither of them.

Which has the bigger context window, R1 0528 or GLM 4.7 Flash?

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

How many benchmarks is the R1 0528 vs GLM 4.7 Flash comparison based on?

43 benchmarks have a result for both models as of October 21, 2026. R1 0528's coding index rests on 0 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.

Compare next