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GLM 5.2 vs MiMo-V2.5-Pro

GLM 5.2 leads MiMo-V2.5-Pro on coding, 61.1 to 31.6 on the Vibe Coding Index, and MiMo-V2.5-Pro costs 4.8x less per output token ($0.9152 vs $4.40 per million). Updated October 22, 2026; 68 benchmarks have a result for both.

Replace GLM 5.2 Replace MiMo-V2.5-Pro
GLM 5.2Z.ai
Coding
61.1
Overall
62.5
Output $/M
$4.40
50
MiMo-V2.5-ProXiaomi
Coding
31.6
Overall
39.3
Output $/M
$0.9152
18
vs boards won of 68 shared

GLM 5.2 or MiMo-V2.5-Pro: which to pick

Pick GLM 5.2 for coding: it scores 61.1 on the Vibe Coding Index against 31.6 for MiMo-V2.5-Pro.

Pick MiMo-V2.5-Pro for output tokens 4.8x cheaper ($0.9152 vs $4.40 per million) and a lower cost per solved task ($0.03 against $0.86).

Model AGLM 5.2Z.ai61.1/1004 independent benchmarks$0.86 per solved taskModel BMiMo-V2.5-ProXiaomi31.6/1004 independent benchmarks$0.03 per solved task
Shared results
68
GLM 5.2 only
30
MiMo-V2.5-Pro 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
GLM 5.2 61.1 from 4 benchmarks, MiMo-V2.5-Pro 31.6 from 4 benchmarks.
Widest category
Coding, 11.3 points apart on average over 14 shared benchmarks.
Widest single gap
Vibe Code Bench (Vals AI): GLM 5.2 64.0% against MiMo-V2.5-Pro 34.1%, 29.9 points apart on a 0 to 100 scale.
Output price
GLM 5.2 $4.40 against MiMo-V2.5-Pro $0.9152 per million output tokens, 4.8x apart.
Context window
GLM 5.2 takes 1.05M tokens, MiMo-V2.5-Pro 1.05M.

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 5.2BarsMiMo-V2.5-ProTies
Coding113
Intelligence10
Agentic work50
Reasoning33
Math21
Knowledge72
Web design80
General139
All shared boards5018
CodingLike-for-likeSix of these boards feed the Vibe Coding Index113
Coding benchmarks for GLM 5.2 and MiMo-V2.5-Pro
BenchmarkGLM 5.2MiMo-V2.5-ProLeader
LMArena WebDev16041480GLM 5.2
AA Coding Index68.860.2GLM 5.2
LiveCodeBench (Vals AI)69.5%81.3%MiMo-V2.5-Pro
SWE-bench Verified (Vals AI)82.8%74.0%GLM 5.2
Terminal-Bench 4 (Vals AI)Not measured0.5%Only MiMo-V2.5-Pro measured
Vibe Code Bench (Vals AI)64.0%34.1%GLM 5.2
Code migration (Vals AI)37.9%21.6%GLM 5.2
ProgramBench (Vals AI)0.5%Not measuredOnly GLM 5.2 measured
Terminal-Bench 2.1 (Vals AI)67.8%57.3%GLM 5.2
SkillsBench (Vals AI)45.1%Not measuredOnly GLM 5.2 measured
SciCode51.2%50.6%GLM 5.2
Terminal-Bench Hard (Artificial Analysis run)50.8%43.2%GLM 5.2
FrontierCode24.5%Not measuredOnly GLM 5.2 measured
WeirdML70.1%Not measuredOnly GLM 5.2 measured
ALE-Bench1047.0899.8GLM 5.2
LMArena Text: coding14871501MiMo-V2.5-Pro
LMArena Text: software and IT14861495MiMo-V2.5-Pro
LMArena WebDev: React16171469GLM 5.2
LMArena WebDev: HTML15651473GLM 5.2
Neither model has a result on the other 20 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for GLM 5.2 and MiMo-V2.5-Pro
BenchmarkGLM 5.2MiMo-V2.5-ProLeader
AA Intelligence Index33.726.0GLM 5.2
Epoch Capabilities Index151.9Not measuredOnly GLM 5.2 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index50
Agentic work benchmarks for GLM 5.2 and MiMo-V2.5-Pro
BenchmarkGLM 5.2MiMo-V2.5-ProLeader
AA Agentic Index38.421.3GLM 5.2
Design Arena: agents building web apps1222Not measuredOnly GLM 5.2 measured
Design Arena: agents building full-stack apps1241Not measuredOnly GLM 5.2 measured
Design Arena: agents building mobile apps1159Not measuredOnly GLM 5.2 measured
Design Arena: agents building Android apps1178Not measuredOnly GLM 5.2 measured
Design Arena: agents building Godot games1142Not measuredOnly GLM 5.2 measured
Design Arena: agents building games1206Not measuredOnly GLM 5.2 measured
Design Arena: HTML slides1125Not measuredOnly GLM 5.2 measured
Design Arena: PowerPoint slides1170Not measuredOnly GLM 5.2 measured
SREBench (Vals AI)0.0%Not measuredOnly GLM 5.2 measured
Finance Agent (Vals AI)49.7%41.5%GLM 5.2
Tax Agent Bench (Vals AI)Not measured11.5%Only MiMo-V2.5-Pro measured
Legal Research Bench (Vals AI)31.3%15.9%GLM 5.2
Excel Modeling Benchmark (Vals AI)61.5%55.2%GLM 5.2
τ²-Bench Telecom99.1%94.2%GLM 5.2
APEX-Agents45.2%Not measuredOnly GLM 5.2 measured
PostTrainBench31.7%Not measuredOnly GLM 5.2 measured
Vending-Bench 2$8,314Not measuredOnly GLM 5.2 measured
Neither model has a result on the other 23 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index33
Reasoning benchmarks for GLM 5.2 and MiMo-V2.5-Pro
BenchmarkGLM 5.2MiMo-V2.5-ProLeader
GPQA Diamond85.6%82.6%GLM 5.2
GPQA Diamond (Artificial Analysis run)89.5%86.6%GLM 5.2
Humanity's Last Exam (Artificial Analysis run)41.1%35.7%GLM 5.2
GPQA Diamond (Epoch AI run)91.9%Not measuredOnly GLM 5.2 measured
ARC-AGI77.0%Not measuredOnly GLM 5.2 measured
ARC-AGI-222.8%Not measuredOnly GLM 5.2 measured
SimpleBench58.8%Not measuredOnly GLM 5.2 measured
Chess puzzles22.0%Not measuredOnly GLM 5.2 measured
Mystery game puzzles19.0%Not measuredOnly GLM 5.2 measured
EBR-bench9.5%Not measuredOnly GLM 5.2 measured
LMArena Text: hard prompts14811486MiMo-V2.5-Pro
LMArena Text: expert14871501MiMo-V2.5-Pro
LMArena Text: hard prompts in English14811494MiMo-V2.5-Pro
Kagi LLM Benchmark62.6%Not measuredOnly GLM 5.2 measured
Neither model has a result on the other 8 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index21
Math benchmarks for GLM 5.2 and MiMo-V2.5-Pro
BenchmarkGLM 5.2MiMo-V2.5-ProLeader
OTIS Mock AIME86.4%Not measuredOnly GLM 5.2 measured
FrontierMath, tiers 1 to 359.2%Not measuredOnly GLM 5.2 measured
FrontierMath, tier 429.3%Not measuredOnly GLM 5.2 measured
ProofBench35.0%22.0%GLM 5.2
LMArena Text: math14831481GLM 5.2
LMArena Text: mathematical work14891491MiMo-V2.5-Pro
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index72
Knowledge benchmarks for GLM 5.2 and MiMo-V2.5-Pro
BenchmarkGLM 5.2MiMo-V2.5-ProLeader
MMLU Pro86.7%84.6%GLM 5.2
LegalBench (Vals AI)84.1%77.1%GLM 5.2
CorpFin (Vals AI)66.1%61.4%GLM 5.2
TaxEval (Vals AI)73.3%73.8%MiMo-V2.5-Pro
MedCode (Vals AI)40.8%32.5%GLM 5.2
SimpleQA Verified34.2%Not measuredOnly GLM 5.2 measured
LMArena Text: science14891482GLM 5.2
LMArena Text: medicine and healthcare14751473GLM 5.2
LMArena Text: legal and government14861474GLM 5.2
LMArena Text: business and finance14511466MiMo-V2.5-Pro
Neither model has a result on the other 8 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index80
Web design benchmarks for GLM 5.2 and MiMo-V2.5-Pro
BenchmarkGLM 5.2MiMo-V2.5-ProLeader
Design Arena: websites12851266GLM 5.2
Design Arena: UI components12941246GLM 5.2
Design Arena: game dev12681261GLM 5.2
Design Arena: data viz12851257GLM 5.2
Design Arena: 3D12871243GLM 5.2
Design Arena: all code categories12871265GLM 5.2
Design Arena: SVG12131181GLM 5.2
Design Arena: ASCII art11911156GLM 5.2
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index139
General benchmarks for GLM 5.2 and MiMo-V2.5-Pro
BenchmarkGLM 5.2MiMo-V2.5-ProLeader
MedScribe (Vals AI)83.5%83.7%MiMo-V2.5-Pro
IFBench73.3%79.9%MiMo-V2.5-Pro
Long context reasoning (AA-LCR)78.3%79.7%MiMo-V2.5-Pro
DTBench93.6%84.5%GLM 5.2
LMCA45.8%29.5%GLM 5.2
Surface Evolver Bench55.6%Not measuredOnly GLM 5.2 measured
LMArena Text14701464GLM 5.2
LMArena Text: instruction following14661475MiMo-V2.5-Pro
LMArena Text: creative writing14631438GLM 5.2
LMArena Text: English14751477MiMo-V2.5-Pro
LMArena Text: non-English14591448GLM 5.2
LMArena Text: Chinese15221507GLM 5.2
LMArena Text: German14701459GLM 5.2
LMArena Text: Japanese14501410GLM 5.2
LMArena Text: Korean14401435GLM 5.2
LMArena Text: French14791487MiMo-V2.5-Pro
LMArena Text: Spanish14781469GLM 5.2
LMArena Text: Russian14681449GLM 5.2
LMArena Text: Polish14561464MiMo-V2.5-Pro
LMArena Text: multi-turn14691476MiMo-V2.5-Pro
LMArena Text: longer queries14801481MiMo-V2.5-Pro
LMArena Text: writing and language14631451GLM 5.2
LMArena Text: entertainment and media14501438GLM 5.2
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 GLM 5.2 and MiMo-V2.5-Pro
BenchmarkGLM 5.2MiMo-V2.5-ProLeader
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 5.2$0.0036Fits in one request
MiMo-V2.5-Pro$0.0009Fits in one request

MiMo-V2.5-Pro costs less

Repository review

50K input + 3K output tokens

GLM 5.2$0.083Fits in one request
MiMo-V2.5-Pro$0.026Fits in one request

MiMo-V2.5-Pro costs less

Agent loop

200K input + 10K output tokens

GLM 5.2$0.324Fits in one request
MiMo-V2.5-Pro$0.101Fits in one request

MiMo-V2.5-Pro 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 5.2 and MiMo-V2.5-Pro
SpecificationZ.ai GLM 5.2Xiaomi MiMo-V2.5-Pro
MakerZ.aiXiaomi
WeightsOpen weightsOpen weights
ReleasedJune 16, 2026April 22, 2026
Context window1.05M1.05M
Input $/Mtok$1.40$0.4575
Output $/Mtok$4.40$0.9152
Coding index61.131.6
Independent measurements behind it44
Cost per solved task$0.86$0.03
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 5.2 better than MiMo-V2.5-Pro for coding?

Pick GLM 5.2 for coding: it scores 61.1 on the Vibe Coding Index against 31.6 for MiMo-V2.5-Pro. Pick MiMo-V2.5-Pro for output tokens 4.8x cheaper ($0.9152 vs $4.40 per million) and a lower cost per solved task ($0.03 against $0.86).

Which is cheaper, GLM 5.2 or MiMo-V2.5-Pro?

GLM 5.2 costs $1.40 per million input tokens and $4.40 per million output tokens; MiMo-V2.5-Pro costs $0.4575 and $0.9152. Per solved SWE-bench Verified task, GLM 5.2 costs $0.86 and MiMo-V2.5-Pro $0.03.

Which has the bigger context window, GLM 5.2 or MiMo-V2.5-Pro?

MiMo-V2.5-Pro, with 1.05M tokens against 1.05M.

How many benchmarks is the GLM 5.2 vs MiMo-V2.5-Pro comparison based on?

68 benchmarks have a result for both models as of October 22, 2026. GLM 5.2's coding index rests on 4 independent benchmarks and MiMo-V2.5-Pro's on 4. Where only one model has a result, the page says so instead of naming a winner.

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