LLMBenchmark.ai

Enter opens the highlighted result. Esc closes.

GLM 5 vs Mercury 2

Updated October 21, 2026. 39 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace GLM 5 Replace Mercury 2
GLM 5Z.ai
Coding
59.7
Overall
27.9
Output $/M
$3.20
38
Mercury 2Inception
Coding
0.0
Overall
10.8
Output $/M
$0.75
1
vs boards won of 39 shared

Decision reading

Pick GLM 5 for coding: it scores 59.7 on the Vibe Coding Index against 0.0 for Mercury 2.

Pick Mercury 2 when output tokens cost 4.3x less, or when the benchmark that matters is ALE-Bench, where it leads.

Model AGLM 5Z.ai59.7/1002 independent benchmarks$0.63 per solved taskModel BMercury 2Inception0.0/1001 independent benchmarkNo cost per solved task
Shared results
39
GLM 5 only
36
Mercury 2 only
3
Like-for-like categories
7 of 9

Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.

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
GLM 5 59.7 from 2 benchmarks, Mercury 2 0.0 from 1 benchmark.
Widest category
Agentic work, 27.5 points apart on average over 1 shared benchmark.
Widest single gap
LMArena WebDev: React: GLM 5 1424 against Mercury 2 1160, 44.1 points apart on a 0 to 100 scale.
Output price
GLM 5 $3.20 against Mercury 2 $0.75 per million output tokens, 4.3x apart.
Context window
GLM 5 takes 205K tokens, Mercury 2 128K.

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
CategoryGLM 5BarsMercury 2Ties
Coding71
Intelligence10
Agentic work10
Reasoning50
Knowledge30
Web design80
General130
All shared boards381
CodingLike-for-likeFour of these boards feed the Vibe Coding Index71
Coding benchmarks for GLM 5 and Mercury 2
BenchmarkGLM 5Mercury 2Leader
SWE-bench Verified72.8%Not measuredOnly GLM 5 measured
SWE-bench Multilingual69.7%Not measuredOnly GLM 5 measured
LMArena WebDev14351171GLM 5
AA Coding IndexNot measured31.1Only Mercury 2 measured
LiveCodeBench (Vals AI)81.9%Not measuredOnly GLM 5 measured
SWE-bench Verified (Vals AI)71.4%Not measuredOnly GLM 5 measured
Vibe Code Bench (Vals AI)23.4%Not measuredOnly GLM 5 measured
SciCodeNot measured37.7%Only Mercury 2 measured
Terminal-Bench Hard (Artificial Analysis run)43.2%26.5%GLM 5
Terminal-Bench52.4%Not measuredOnly GLM 5 measured
WeirdML48.2%43.2%GLM 5
ALE-Bench765.6785.6Mercury 2
LMArena Text: coding14611390GLM 5
LMArena Text: software and IT14601385GLM 5
LMArena WebDev: React14241160GLM 5
LMArena WebDev: HTML14501199GLM 5
Neither model has a result on the other 22 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for GLM 5 and Mercury 2
BenchmarkGLM 5Mercury 2Leader
AA Intelligence Index27.910.8GLM 5
Epoch Capabilities Index145.8Not measuredOnly GLM 5 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for GLM 5 and Mercury 2
BenchmarkGLM 5Mercury 2Leader
AA Agentic IndexNot measured1.6Only Mercury 2 measured
Design Arena: agents building full-stack apps1123Not measuredOnly GLM 5 measured
Design Arena: agents building mobile apps1136Not measuredOnly GLM 5 measured
Design Arena: agents building Android apps1152Not measuredOnly GLM 5 measured
Design Arena: agents building Godot games1144Not measuredOnly GLM 5 measured
Design Arena: HTML slides1148Not measuredOnly GLM 5 measured
τ²-Bench Telecom98.2%70.8%GLM 5
Vending-Bench 2$4,432Not measuredOnly GLM 5 measured
Neither model has a result on the other 31 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index50
Reasoning benchmarks for GLM 5 and Mercury 2
BenchmarkGLM 5Mercury 2Leader
GPQA Diamond83.3%Not measuredOnly GLM 5 measured
GPQA Diamond (Artificial Analysis run)82.0%77.0%GLM 5
Humanity's Last Exam (Artificial Analysis run)29.3%17.1%GLM 5
GPQA Diamond (Epoch AI run)87.8%Not measuredOnly GLM 5 measured
ARC-AGI44.7%Not measuredOnly GLM 5 measured
ARC-AGI-24.9%Not measuredOnly GLM 5 measured
SimpleBench53.2%Not measuredOnly GLM 5 measured
LMArena Text: hard prompts14521362GLM 5
LMArena Text: expert14541358GLM 5
LMArena Text: hard prompts in English14601374GLM 5
Neither model has a result on the other 11 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
Math benchmarks for GLM 5 and Mercury 2
BenchmarkGLM 5Mercury 2Leader
AIME91.7%Not measuredOnly GLM 5 measured
OTIS Mock AIME80.0%Not measuredOnly GLM 5 measured
LMArena Text: math1440Not measuredOnly GLM 5 measured
LMArena Text: mathematical work1451Not measuredOnly GLM 5 measured
Neither model has a result on the other 9 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index30
Knowledge benchmarks for GLM 5 and Mercury 2
BenchmarkGLM 5Mercury 2Leader
MMLU Pro86.0%Not measuredOnly GLM 5 measured
LegalBench (Vals AI)84.1%Not measuredOnly GLM 5 measured
CaseLaw (Vals AI)52.5%Not measuredOnly GLM 5 measured
CorpFin (Vals AI)62.9%Not measuredOnly GLM 5 measured
TaxEval (Vals AI)70.0%Not measuredOnly GLM 5 measured
MedQA (Vals AI)94.3%Not measuredOnly GLM 5 measured
LMArena Text: science14601343GLM 5
LMArena Text: medicine and healthcare14551363GLM 5
LMArena Text: legal and government1453Not measuredOnly GLM 5 measured
LMArena Text: business and finance14301349GLM 5
Neither model has a result on the other 7 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index80
Web design benchmarks for GLM 5 and Mercury 2
BenchmarkGLM 5Mercury 2Leader
Design Arena: websites12471036GLM 5
Design Arena: UI components1230998GLM 5
Design Arena: game dev1234985GLM 5
Design Arena: data viz12281009GLM 5
Design Arena: 3D1229982GLM 5
Design Arena: all code categories12461022GLM 5
Design Arena: SVG1168998GLM 5
Design Arena: ASCII art1146990GLM 5
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index130
General benchmarks for GLM 5 and Mercury 2
BenchmarkGLM 5Mercury 2Leader
IFBench72.3%69.8%GLM 5
Long context reasoning (AA-LCR)75.7%43.7%GLM 5
CL-bench18.7%Not measuredOnly GLM 5 measured
LMArena Text14461354GLM 5
LMArena Text: instruction following14281328GLM 5
LMArena Text: creative writing14381286GLM 5
LMArena Text: English14581378GLM 5
LMArena Text: non-English14301330GLM 5
LMArena Text: Chinese15111414GLM 5
LMArena Text: German1447Not measuredOnly GLM 5 measured
LMArena Text: Japanese1416Not measuredOnly GLM 5 measured
LMArena Text: Korean1423Not measuredOnly GLM 5 measured
LMArena Text: French1456Not measuredOnly GLM 5 measured
LMArena Text: Spanish1454Not measuredOnly GLM 5 measured
LMArena Text: Russian14361304GLM 5
LMArena Text: Polish1434Not measuredOnly GLM 5 measured
LMArena Text: multi-turn14561357GLM 5
LMArena Text: longer queries14461329GLM 5
LMArena Text: writing and language14371300GLM 5
LMArena Text: entertainment and media14261314GLM 5
Neither model has a result on the other 26 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GLM 5 and Mercury 2
BenchmarkGLM 5Mercury 2Leader
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

GLM 5$0.0026Fits in one request
Mercury 2$0.0006Fits in one request

Mercury 2 costs less

Repository review

50K input + 3K output tokens

GLM 5$0.060Fits in one request
Mercury 2$0.015Fits in one request

Mercury 2 costs less

Agent loop

200K input + 10K output tokens

GLM 5$0.232Exceeds the context window
Mercury 2$0.058Exceeds the context window

Mercury 2 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 GLM 5 and Mercury 2
SpecificationZ.ai GLM 5Inception Mercury 2
MakerZ.aiInception
WeightsOpen weightsNo public weights listed
ReleasedFebruary 11, 2026March 4, 2026
Context window205K128K
Input $/Mtok$1.00$0.25
Output $/Mtok$3.20$0.75
Coding index59.70.0
Independent measurements behind it21
Cost per solved task$0.63Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 5 better than Mercury 2 for coding?

Pick GLM 5 for coding: it scores 59.7 on the Vibe Coding Index against 0.0 for Mercury 2. Pick Mercury 2 when output tokens cost 4.3x less, or when the benchmark that matters is ALE-Bench, where it leads.

Which is cheaper, GLM 5 or Mercury 2?

GLM 5 costs $1.00 per million input tokens and $3.20 per million output tokens; Mercury 2 costs $0.25 and $0.75. Cost per solved task is known for GLM 5 only.

Which has the bigger context window, GLM 5 or Mercury 2?

GLM 5, with 205K tokens against 128K.

How many benchmarks is the GLM 5 vs Mercury 2 comparison based on?

39 benchmarks have a result for both models as of October 21, 2026. GLM 5's coding index rests on 2 independent benchmarks and Mercury 2's on 1. Where only one model has a result, the page says so instead of naming a winner.

Compare next