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Model profile

GLM-5 (Reasoning)

Z.AICurrentReleased Mar 1, 2026
Data verified
Overall Score
59.77Public #52 of 200
Arena Elo
1456
Eligible category ranks
0of 8
Price (1M tokens)
$1 in / $3.2 out
API pricing
Speed
Not listed
Context
200K

Evidence coverage

2 of 321 tracked benchmarks are published. 1 is verified and 1 provisional. 2 of 8 categories are measured.

Updated July 20, 2026Methodology
Published / tracked
2 / 321
Verified
1
Provisional
1
Categories with evidence
2 / 8

Evidence by category

  • Agentic0 benchmarks
    Not measured
  • Coding1 benchmark
    Verified
  • Reasoning0 benchmarks
    Not measured
  • Knowledge0 benchmarks
    Not measured
  • Math0 benchmarks
    Not measured
  • Multilingual0 benchmarks
    Not measured
  • Multimodal1 benchmark
    Reported
  • Inst. Following0 benchmarks
    Not measured
Open WeightSelf-hostReasoning
Confidence:
Low
reasoning

GLM-5 (Reasoning) ranks #52 out of 200 models on the public leaderboard with an overall score of 59.77/100. It does not yet have enough sourced coverage for BenchLM's verified leaderboard. While not a frontier model, it offers specific advantages depending on the use case.

GLM-5 (Reasoning) is a open weight model with a 200K token context window. It uses explicit chain-of-thought reasoning, which typically improves performance on math and complex reasoning tasks at the cost of higher latency and token usage.

GLM-5 (Reasoning) sits inside the GLM-5 family alongside GLM-5, GLM-5.2, GLM-5.1, GLM-5-Turbo, GLM-5V-Turbo. This profile currently has 2 of 321 tracked benchmarks. BenchLM only exposes non-generated benchmark rows publicly, so missing categories stay blank until a sourced evaluation is available.

Peer position

Exact provisional scores and ranks for the closest listed peers. A score can appear before a model clears the evidence threshold for a rank, so equal scores can have different rank states.

Range 59.3559.97

  1. Grok 4.1
    xAI
    #5159.97
    Grok 4.1 is #51 with a score of 59.97.
    Compare
  2. GLM-5 (Reasoning)Current model
    Z.AI
    #5259.77
    GLM-5 (Reasoning) is #52 with a score of 59.77.
  3. Qwen 3.6 Max (preview)
    Alibaba
    #5359.72
    Qwen 3.6 Max (preview) is #53 with a score of 59.72.
    Compare
  4. Kimi K2.5
    Moonshot AI
    #5459.66
    Kimi K2.5 is #54 with a score of 59.66.
    Compare
  5. MiniMax M2.5
    MiniMax
    #5559.52
    MiniMax M2.5 is #55 with a score of 59.52.
    Compare
  6. Qwen3.5 397B (Reasoning)
    Alibaba
    #5659.5
    Qwen3.5 397B (Reasoning) is #56 with a score of 59.5.
    Compare
  7. Kimi K2.5 (Reasoning)
    Moonshot AI
    #5759.35
    Kimi K2.5 (Reasoning) is #57 with a score of 59.35.
    Compare

Category percentile

More

Relative position among models eligible for each sourced category. A higher percentile means a stronger position within that category's ranked cohort; 100 is highest.

No eligible category percentile is available from the published evidence yet.

Category evidence

Scores and ranks appear only where this model has published benchmark evidence. Categories without displayable source records remain not measured.

Category scores, ranks, weighting, benchmark coverage, and evidence status
CategoryScore
AgenticWeight 22%0 benchmarksNot measuredNot measured
CodingRank Not rankedWeight 20%1 benchmarkVerified57.2
ReasoningWeight 17%0 benchmarksNot measuredNot measured
KnowledgeWeight 12%0 benchmarksNot measuredNot measured
MathWeight 5%0 benchmarksNot measuredNot measured
MultilingualWeight 7%0 benchmarksNot measuredNot measured
MultimodalRank Not rankedWeight 12%1 benchmarkReported78.0
Inst. FollowingWeight 5%0 benchmarksNot measuredNot measured

Chatbot Arena performance

Scroll horizontally to inspect confidence intervals and vote counts.

Chatbot Arena Elo, confidence interval, and vote count by evaluation view
ViewEloConfidence intervalVotes
Text Overall1456±6.011,101
Coding1491±11.62,492
Math1455±21.0717
Instruction Following1445±10.43,132
Creative Writing1442±14.61,725
Multi-turn1457±13.91,747
Hard Prompts1476±7.66,159
Hard Prompts (English)1480±10.92,816
Longer Query1462±10.43,140

Benchmark Details

Rows below have a displayable published verification record. Each source link and provenance note remains in the page HTML while its category is closed. Source-unverified manual rows and generated rows stay hidden.

Coding1 benchmark
Vibe Code BenchBenchmark exact

Vibe Code Bench v1.1

23.36%Display only
Source: Vals AI: Vibe Code Bench v1.1Provenance: Vals Vibe Code Bench v1.1 reports this exact row under zai/glm-5-thinking; BenchLM stores it on the local vibeCodeBench key.
Multimodal1 benchmark
Design Arena WebsiteReported

Design Arena Website Elo

1280Display only
Source: OpenRouter model benchmarksProvenance: Display-only Design Arena Website Elo synced from OpenRouter model benchmark metadata. It is excluded from BenchLM weighted scoring.

Frequently Asked Questions

How does GLM-5 (Reasoning) perform overall in AI benchmarks?

GLM-5 (Reasoning) has 2 published benchmark scores on BenchLM, but it does not yet have enough non-generated coverage to receive a global overall rank.

Is GLM-5 (Reasoning) good for coding and programming?

GLM-5 (Reasoning) has visible benchmark coverage in coding and programming, but BenchLM does not currently assign it a global category rank there.

Is GLM-5 (Reasoning) good for multimodal and grounded tasks?

GLM-5 (Reasoning) has visible benchmark coverage in multimodal and grounded tasks, but BenchLM does not currently assign it a global category rank there.

Is GLM-5 (Reasoning) open source?

Yes, GLM-5 (Reasoning) is an open weight model created by Z.AI, meaning it can be downloaded and run locally or fine-tuned for specific use cases.

Which sibling models are related to GLM-5 (Reasoning)?

GLM-5 (Reasoning) belongs to the GLM-5 family. Related variants on BenchLM include GLM-5, GLM-5.2, GLM-5.1, GLM-5-Turbo, GLM-5V-Turbo.

Does GLM-5 (Reasoning) have full benchmark coverage on BenchLM?

Not yet. GLM-5 (Reasoning) currently has 2 published benchmark scores out of the 321 benchmarks BenchLM tracks. BenchLM only exposes non-generated public benchmark rows, so missing categories stay blank until a sourced evaluation is available.

What is the context window size of GLM-5 (Reasoning)?

GLM-5 (Reasoning) has a published context window of 200K, which determines how much text it can process in a single interaction.

Last updated: July 20, 2026 · Runtime metrics stay blank until BenchLM has a sourced snapshot.

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