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GLM 4.5 vs Mercury 2

GLM 4.5 leads Mercury 2 on the Artificial Analysis Intelligence Index, 12.8 to 10.8, and Mercury 2 costs 2.9x less per output token ($0.75 vs $2.20 per million). Updated October 22, 2026; 35 benchmarks have a result for both.

Replace GLM 4.5 Replace Mercury 2
GLM 4.5Z.ai
Coding
No data
Overall
No data
Output $/M
$2.20
29
Mercury 2Inception
Coding
No data
Overall
No data
Output $/M
$0.75
6
vs boards won of 35 shared

GLM 4.5 or Mercury 2: which to pick

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

Pick GLM 4.5 for a larger context window (131K against 128K tokens) and work measured by Terminal-Bench Hard (Artificial Analysis run) or WeirdML, where it leads.

Model AGLM 4.5Z.aiNot benchmarkedNo coding benchmarkNo cost per solved taskModel BMercury 2InceptionNot benchmarked1 independent benchmarkNo cost per solved task
Shared results
35
GLM 4.5 only
26
Mercury 2 only
7
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
GLM 4.5 not benchmarked, Mercury 2 not benchmarked.
Widest category
Agentic work, 27.8 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: GLM 4.5 43.0% against Mercury 2 70.8%, 27.8 points apart on a 0 to 100 scale.
Output price
GLM 4.5 $2.20 against Mercury 2 $0.75 per million output tokens, 2.9x apart.
Context window
GLM 4.5 takes 131K 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 4.5BarsMercury 2Ties
Coding23
Intelligence10
Agentic work01
Reasoning41
Knowledge30
Web design70
General121
All shared boards296
CodingLike-for-likeSix of these boards feed the Vibe Coding Index23
Coding benchmarks for GLM 4.5 and Mercury 2
BenchmarkGLM 4.5Mercury 2Leader
SWE-bench Verified64.2%Not measuredOnly GLM 4.5 measured
LMArena WebDevNot measured1171Only Mercury 2 measured
AA Coding IndexNot measured31.1Only Mercury 2 measured
LiveCodeBench (Vals AI)67.5%Not measuredOnly GLM 4.5 measured
LiveCodeBench (Artificial Analysis run)73.8%Not measuredOnly GLM 4.5 measured
SciCodeNot measured37.7%Only Mercury 2 measured
Terminal-Bench Hard (Artificial Analysis run)22.0%26.5%Mercury 2
WeirdML40.6%43.2%Mercury 2
ALE-Bench344.8785.6Mercury 2
LMArena Text: coding14341390GLM 4.5
LMArena Text: software and IT14401385GLM 4.5
LMArena WebDev: ReactNot measured1160Only Mercury 2 measured
LMArena WebDev: HTMLNot measured1199Only Mercury 2 measured
Neither model has a result on the other 26 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for GLM 4.5 and Mercury 2
BenchmarkGLM 4.5Mercury 2Leader
AA Intelligence Index12.810.8GLM 4.5
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 GLM 4.5 and Mercury 2
BenchmarkGLM 4.5Mercury 2Leader
AA Agentic IndexNot measured1.6Only Mercury 2 measured
τ²-Bench Telecom43.0%70.8%Mercury 2
Neither model has a result on the other 39 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index41
Reasoning benchmarks for GLM 4.5 and Mercury 2
BenchmarkGLM 4.5Mercury 2Leader
GPQA Diamond72.2%Not measuredOnly GLM 4.5 measured
GPQA Diamond (Artificial Analysis run)78.2%77.0%GLM 4.5
Humanity's Last Exam (Artificial Analysis run)13.0%17.1%Mercury 2
LMArena Text: hard prompts14291362GLM 4.5
LMArena Text: expert14331358GLM 4.5
LMArena Text: hard prompts in English14291374GLM 4.5
Kagi LLM Benchmark57.9%Not measuredOnly GLM 4.5 measured
Neither model has a result on the other 15 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
Math benchmarks for GLM 4.5 and Mercury 2
BenchmarkGLM 4.5Mercury 2Leader
AIME86.7%Not measuredOnly GLM 4.5 measured
MATH 500 (Vals AI)94.0%Not measuredOnly GLM 4.5 measured
MGSM (Vals AI)90.8%Not measuredOnly GLM 4.5 measured
AA Math Index73.7Not measuredOnly GLM 4.5 measured
AIME 2025 (Artificial Analysis run)73.7%Not measuredOnly GLM 4.5 measured
LMArena Text: math1427Not measuredOnly GLM 4.5 measured
LMArena Text: mathematical work1430Not measuredOnly GLM 4.5 measured
Neither model has a result on the other 6 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index30
Knowledge benchmarks for GLM 4.5 and Mercury 2
BenchmarkGLM 4.5Mercury 2Leader
MMLU Pro81.2%Not measuredOnly GLM 4.5 measured
LegalBench (Vals AI)75.6%Not measuredOnly GLM 4.5 measured
CorpFin (Vals AI)61.0%Not measuredOnly GLM 4.5 measured
TaxEval (Vals AI)72.4%Not measuredOnly GLM 4.5 measured
MedQA (Vals AI)90.0%Not measuredOnly GLM 4.5 measured
MMLU Pro (Artificial Analysis run)83.5%Not measuredOnly GLM 4.5 measured
LMArena Text: science14441343GLM 4.5
LMArena Text: medicine and healthcare14551363GLM 4.5
LMArena Text: legal and government1438Not measuredOnly GLM 4.5 measured
LMArena Text: business and finance14201349GLM 4.5
Neither model has a result on the other 8 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index70
Web design benchmarks for GLM 4.5 and Mercury 2
BenchmarkGLM 4.5Mercury 2Leader
Design Arena: websites11691036GLM 4.5
Design Arena: UI components1141996GLM 4.5
Design Arena: game dev1144984GLM 4.5
Design Arena: data viz11591009GLM 4.5
Design Arena: 3D1170982GLM 4.5
Design Arena: all code categories11651021GLM 4.5
Design Arena: SVG1096998GLM 4.5
Design Arena: ASCII artNot measured988Only Mercury 2 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index121
General benchmarks for GLM 4.5 and Mercury 2
BenchmarkGLM 4.5Mercury 2Leader
IFBench44.1%69.8%Mercury 2
Long context reasoning (AA-LCR)52.7%43.7%GLM 4.5
Creative writing (Lech Mazur)73.4%Not measuredOnly GLM 4.5 measured
LMArena Text14301354GLM 4.5
LMArena Text: instruction following14041328GLM 4.5
LMArena Text: creative writing13951286GLM 4.5
LMArena Text: English14371378GLM 4.5
LMArena Text: non-English14171330GLM 4.5
LMArena Text: Chinese14651414GLM 4.5
LMArena Text: German1407Not measuredOnly GLM 4.5 measured
LMArena Text: Japanese1415Not measuredOnly GLM 4.5 measured
LMArena Text: Korean1380Not measuredOnly GLM 4.5 measured
LMArena Text: French1418Not measuredOnly GLM 4.5 measured
LMArena Text: Spanish1454Not measuredOnly GLM 4.5 measured
LMArena Text: Russian14131304GLM 4.5
LMArena Text: Polish1422Not measuredOnly GLM 4.5 measured
LMArena Text: multi-turn14151357GLM 4.5
LMArena Text: longer queries14121329GLM 4.5
LMArena Text: writing and language14031300GLM 4.5
LMArena Text: entertainment and media14041314GLM 4.5
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 4.5 and Mercury 2
BenchmarkGLM 4.5Mercury 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 4.5$0.0017Fits in one request
Mercury 2$0.0006Fits in one request

Mercury 2 costs less

Repository review

50K input + 3K output tokens

GLM 4.5$0.037Fits in one request
Mercury 2$0.015Fits in one request

Mercury 2 costs less

Agent loop

200K input + 10K output tokens

GLM 4.5$0.142Exceeds 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 4.5 and Mercury 2
SpecificationZ.ai GLM 4.5Inception Mercury 2
MakerZ.aiInception
WeightsOpen weightsNo public weights listed
ReleasedJuly 25, 2025March 4, 2026
Context window131K128K
Input $/Mtok$0.60$0.25
Output $/Mtok$2.20$0.75
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it01
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 4.5 better than Mercury 2 for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GLM 4.5 for a larger context window (131K against 128K tokens) and work measured by Terminal-Bench Hard (Artificial Analysis run) or WeirdML, where it leads.

Which is cheaper, GLM 4.5 or Mercury 2?

GLM 4.5 costs $0.60 per million input tokens and $2.20 per million output tokens; Mercury 2 costs $0.25 and $0.75. Cost per solved task is known for neither of them.

Which has the bigger context window, GLM 4.5 or Mercury 2?

GLM 4.5, with 131K tokens against 128K.

How many benchmarks is the GLM 4.5 vs Mercury 2 comparison based on?

35 benchmarks have a result for both models as of October 22, 2026. GLM 4.5's coding index rests on 0 independent benchmarks and Mercury 2's on 1. Where only one model has a result, the page says so instead of naming a winner.

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