# GLM-4.5

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Z.ai

Canonical URL: https://benchize.com/models/glm-4-5
Last updated: Thu, 22 Oct 2026 06:20:09 GMT

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Z.ai

## Benchmarks

| Benchmark | Score | ± | Rank | Cost | Source |  |
| --- | --- | --- | --- | --- | --- | --- |
| [Slop Score](https://benchize.com/benchmarks/eq-bench%3Aslop-score.md) | 59.93% | — | 11 / 16 | — | [eq bench · slop-score](https://eqbench.com/data/leaderboard_results.json) |  |
| ### Original source values \| Metric \| Value \| Unit \| Scope \| Direction \| \| --- \| --- \| --- \| --- \| --- \| \| `slop_score` \| 59.93007991040196 \| percent \| official_normalized_composite \| Lower is better \| \| `slop_list_matches_per_1k_words` \| 28.446055294314608 \| matches_per_1000_words \| writing_samples \| Lower is better \| \| `slop_trigram_matches_per_1k_words` \| 0.7900866158152431 \| matches_per_1000_words \| writing_samples \| Lower is better \| \| `not_x_but_y_per_1k_chars` \| 0.42388987350114976 \| matches_per_1000_chars \| writing_samples \| Lower is better \| ### Configuration normalization official_population_min_max_10_percent_buffer protocol slop-score ### Reported statistics samples 299 ### Source [Original source](https://eqbench.com/data/leaderboard_results.json) Source eq bench Original model label z-ai/glm-4.5 Source version slop-score Evaluated 2025-11-01T08:48:31.386328+00:00 Observed 2026-10-22T05:10:07.984Z Evidence SHA-256 `16925b79d955a1cacef4d2ac91b696e73f976a4a3ceb45122544a9cf661b04de` Source locator `/results/17` |  |  |  |  |  |  |
| [SWE-bench Verified](https://benchize.com/benchmarks/swe-bench%3Averified.md) | 64.2% | — | 21 / 63 | — | [SWE-bench](https://www.swebench.com/) |  |
| ### Original source values \| Metric \| Value \| Unit \| Scope \| Direction \| \| --- \| --- \| --- \| --- \| --- \| \| `resolved` \| 64.2 \| percent \| verified \| Higher is better \| ### Configuration agent Undisclosed agentOrganization Z.ai models ["https://huggingface.co/zai-org/GLM-4.5"] Reasoning effort Not reported sourceSubmission 20250728_zai_glm4-5 subset Verified system ["System: Attempts - 1"] ### Source [Original source](https://www.swebench.com/) Source SWE-bench Original model label GLM-4.5 Observed 2026-10-22T02:30:05.773Z Evidence SHA-256 `c862011a4ee1d1a7199fad6ca0905fa5c64f58216f7217ac1eddf37f28788433` Source locator `/leaderboard-data/2/results/65` |  |  |  |  |  |  |
| [Judgemark v2.1](https://benchize.com/benchmarks/eq-bench%3Ajudgemark-v2.md) | 63.41% | — | 27 / 39 | — | [eq bench · judgemark-v2](https://eqbench.com/judgemark-v2.js) |  |
| ### Original source values \| Metric \| Value \| Unit \| Scope \| Direction \| \| --- \| --- \| --- \| --- \| --- \| \| `judgemark_score` \| 63.41 \| percent \| overall \| Higher is better \| \| `stability` \| 0.53 \| score_fraction \| overall \| Higher is better \| \| `separability` \| 0.664 \| score_fraction \| overall \| Higher is better \| \| `human_corr` \| 0.619 \| correlation \| overall \| Higher is better \| ### Configuration interactiveAdjustments none protocol judgemark-v2 sourceModelVersion z-ai/glm-4.5 ### Source [Original source](https://eqbench.com/judgemark-v2.js) Source eq bench Original model label z-ai/glm-4.5 Source version judgemark-v2 Observed 2026-10-22T05:10:06.632Z Evidence SHA-256 `070cc3fbd6f0333dde2b52bec4329ea3fba7eccbf016bbbbef95e0f8b2197781` Source locator `/leaderboardDataV2/5` |  |  |  |  |  |  |
| [EQ-Bench 3](https://benchize.com/benchmarks/eq-bench%3Aeqbench3.md) | 1,276.3elo | CI 1,232.7–1,320 | 27 / 50 | — | [eq bench · eqbench3](https://eqbench.com/eqbench3.js) |  |
| ### Original source values \| Metric \| Value \| Unit \| Scope \| Direction \| \| --- \| --- \| --- \| --- \| --- \| \| `elo_norm` \| 1276.3 \| elo \| overall \| Higher is better \| \| `rubric_0_100` \| 67.4 \| percent \| overall \| Higher is better \| ### Configuration interactiveAdjustments none protocol eqbench3 sourceModelVersion zai-org/GLM-4.5 ### Reported statistics Uncertainty Confidence interval: 1,232.7–1,320 confidenceIntervalHigh 1320.0 confidenceIntervalLow 1232.7 ### Source [Original source](https://eqbench.com/eqbench3.js) Source eq bench Original model label zai-org/GLM-4.5 Source version eqbench3 Observed 2026-10-22T05:10:04.922Z Evidence SHA-256 `3672ff093e739f07ff664a2e6013bc38a6977a146e4092b4cef80ba1780542b2` Source locator `/leaderboardDataEQBench3/37` |  |  |  |  |  |  |
| [BRUMO 2025](https://benchize.com/benchmarks/matharena%3Abrumo--brumo_2025.md) | 92.5% | 95% CI 87.79–97.21% | 9 / 26 | 0.04usd per problem | [matharena · brumo--brumo_2025](https://matharena.ai/competition_tables/brumo--brumo_2025) |  |
| ### Original source values \| Metric \| Value \| Unit \| Scope \| Direction \| \| --- \| --- \| --- \| --- \| --- \| \| `accuracy` \| 92.50 \| percent \| competition \| Higher is better \| \| `cost_per_problem` \| 0.043 \| usd_per_problem \| competition \| Lower is better \| ### Configuration competition brumo--brumo_2025 predicted false sourceModelName GLM 4.5 sourceModelVersion glm/glm-45 ### Reported statistics Uncertainty 95% confidence interval: 87.79–97.21% confidenceInterval95 4.71 problems 30 ### Source [Original source](https://matharena.ai/competition_tables/brumo--brumo_2025) Source matharena Original model label GLM 4.5 Source version brumo--brumo_2025 Observed 2026-10-22T05:30:12.351Z Evidence SHA-256 `d1d1c126b1feff70b2bcc20a7adbf380d94c2aaab0704704cb01593d4e1958ff` Source locator `/table/rows/18` |  |  |  |  |  |  |
| [SWE-bench Verified](https://benchize.com/benchmarks/swe-bench%3Averified.md) | 54.2% | — | 35 / 63 | — | [SWE-bench](https://www.swebench.com/) |  |
| ### Original source values \| Metric \| Value \| Unit \| Scope \| Direction \| \| --- \| --- \| --- \| --- \| --- \| \| `resolved` \| 54.2 \| percent \| verified \| Higher is better \| ### Configuration agent mini-SWE-agent agentOrganization SWE-agent models ["GLM-4.5"] Reasoning effort Not reported sourceSubmission 20250822_mini-v1.9.1_glm-4.5 subset Verified system ["System: Attempts - 1"] ### Reported statistics instanceCalls 40.224 instanceCost 0.2971903488 sourceWarning Not reported ### Source [Original source](https://www.swebench.com/) Source SWE-bench Original model label GLM 4.5 Observed 2026-10-22T02:30:05.773Z Evidence SHA-256 `c862011a4ee1d1a7199fad6ca0905fa5c64f58216f7217ac1eddf37f28788433` Source locator `/leaderboard-data/2/results/94` |  |  |  |  |  |  |
| [Creative Writing v3](https://benchize.com/benchmarks/eq-bench%3Acreative-writing-v3.md) | 1,343.3elo | — | 66 / 90 | — | [eq bench · creative-writing-v3](https://eqbench.com/creative_writing.js) |  |
| ### Original source values \| Metric \| Value \| Unit \| Scope \| Direction \| \| --- \| --- \| --- \| --- \| --- \| \| `elo_score` \| 1343.3 \| elo \| overall \| Higher is better \| \| `creative_writing_score` \| 15.83 \| rubric_score \| overall \| Higher is better \| ### Configuration interactiveAdjustments none protocol creative-writing-v3 sourceModelVersion zai-org/GLM-4.5 ### Source [Original source](https://eqbench.com/creative_writing.js) Source eq bench Original model label zai-org/GLM-4.5 Source version creative-writing-v3 Observed 2026-10-22T05:10:05.433Z Evidence SHA-256 `722ddb132e8d3a5e5c39b8d445f8475f3f7e24893a007260c6f3e3cce5c1ee18` Source locator `/leaderboardDataCreativeWritingV3/89` |  |  |  |  |  |  |
| [Apex](https://benchize.com/benchmarks/matharena%3Aapex--apex_2025.md) | 1.04% | 95% CI -0.4–2.48% | 22 / 31 | 0.08usd per problem | [matharena · apex--apex_2025](https://matharena.ai/competition_tables/apex--apex_2025) |  |
| ### Original source values \| Metric \| Value \| Unit \| Scope \| Direction \| \| --- \| --- \| --- \| --- \| --- \| \| `accuracy` \| 1.04 \| percent \| competition \| Higher is better \| \| `cost_per_problem` \| 0.076 \| usd_per_problem \| competition \| Lower is better \| ### Configuration competition apex--apex_2025 predicted false sourceModelName GLM 4.5 sourceModelVersion glm/glm-45 ### Reported statistics Uncertainty 95% confidence interval: -0.4–2.48% confidenceInterval95 1.44 problems 12 ### Source [Original source](https://matharena.ai/competition_tables/apex--apex_2025) Source matharena Original model label GLM 4.5 Source version apex--apex_2025 Observed 2026-10-22T05:30:13.849Z Evidence SHA-256 `20b28370d9d7f5a15a19fc9e4226c9857cdb07bc42b32ccec508e687b7b9f3fc` Source locator `/table/rows/37` |  |  |  |  |  |  |
| [CMIMC 2025](https://benchize.com/benchmarks/matharena%3Acmimc--cmimc_2025.md) | 72.5% | 95% CI 65.58–79.42% | 14 / 22 | 0.06usd per problem | [matharena · cmimc--cmimc_2025](https://matharena.ai/competition_tables/cmimc--cmimc_2025) |  |
| ### Original source values \| Metric \| Value \| Unit \| Scope \| Direction \| \| --- \| --- \| --- \| --- \| --- \| \| `accuracy` \| 72.50 \| percent \| competition \| Higher is better \| \| `cost_per_problem` \| 0.060 \| usd_per_problem \| competition \| Lower is better \| ### Configuration competition cmimc--cmimc_2025 predicted false sourceModelName GLM 4.5 sourceModelVersion glm/glm-45 ### Reported statistics Uncertainty 95% confidence interval: 65.58–79.42% confidenceInterval95 6.92 problems 40 ### Source [Original source](https://matharena.ai/competition_tables/cmimc--cmimc_2025) Source matharena Original model label GLM 4.5 Source version cmimc--cmimc_2025 Observed 2026-10-22T05:30:12.870Z Evidence SHA-256 `d5d48c1f54a744d7ff2244bae3258963afdb1ab36fb20464ea9cf47138a1555e` Source locator `/table/rows/23` |  |  |  |  |  |  |
| [SMT 2025](https://benchize.com/benchmarks/matharena%3Asmt--smt_2025.md) | 82.08% | 95% CI 76.92–87.24% | 17 / 26 | 0.05usd per problem | [matharena · smt--smt_2025](https://matharena.ai/competition_tables/smt--smt_2025) |  |
| ### Original source values \| Metric \| Value \| Unit \| Scope \| Direction \| \| --- \| --- \| --- \| --- \| --- \| \| `accuracy` \| 82.08 \| percent \| competition \| Higher is better \| \| `cost_per_problem` \| 0.047 \| usd_per_problem \| competition \| Lower is better \| ### Configuration competition smt--smt_2025 predicted false sourceModelName GLM 4.5 sourceModelVersion glm/glm-45 ### Reported statistics Uncertainty 95% confidence interval: 76.92–87.24% confidenceInterval95 5.16 problems 53 ### Source [Original source](https://matharena.ai/competition_tables/smt--smt_2025) Source matharena Original model label GLM 4.5 Source version smt--smt_2025 Observed 2026-10-22T05:30:12.647Z Evidence SHA-256 `1b4f6f8bafc1688e4557a024513f68befa31aff48fd0623fb4892a61263433b0` Source locator `/table/rows/28` |  |  |  |  |  |  |
| [AIME 2025](https://benchize.com/benchmarks/aime-2025.md) | 93.33% | 95% CI 88.87–97.79% | 8 / 36 | 0.05usd per problem | [matharena · aime--aime_2025](https://matharena.ai/competition_tables/aime--aime_2025) |  |
| ### Original source values \| Metric \| Value \| Unit \| Scope \| Direction \| \| --- \| --- \| --- \| --- \| --- \| \| `accuracy` \| 93.33 \| percent \| competition \| Higher is better \| \| `cost_per_problem` \| 0.048 \| usd_per_problem \| competition \| Lower is better \| ### Configuration competition aime--aime_2025 predicted false sourceModelName GLM 4.5 sourceModelVersion glm/glm-45 ### Reported statistics Uncertainty 95% confidence interval: 88.87–97.79% confidenceInterval95 4.46 problems 30 ### Source [Original source](https://matharena.ai/competition_tables/aime--aime_2025) Source matharena Original model label GLM 4.5 Source version aime--aime_2025 Observed 2026-10-22T05:30:11.892Z Evidence SHA-256 `fab0abcecc4032852ef2cbd2a84d34ffc42202be358b2994bfaba44ae7a0cd9a` Source locator `/table/rows/11` |  |  |  |  |  |  |
| [NC Bench](https://benchize.com/benchmarks/nc-bench%3Aoverall.md) | 84.95% | — | 99 / 144 | — | [nc bench](https://www.nc-bench.com/models) |  |
| ### Original source values \| Metric \| Value \| Unit \| Scope \| Direction \| \| --- \| --- \| --- \| --- \| --- \| \| `score` \| 84.95 \| percent \| reported \| Higher is better \| \| `tooling` \| 98.58 \| percent \| category \| Higher is better \| \| `creative_writing` \| 76.56 \| percent \| category \| Higher is better \| \| `language` \| 97.33 \| percent \| category \| Higher is better \| \| `utility` \| 79.19 \| percent \| category \| Higher is better \| \| `reasoning` \| 77 \| percent \| category \| Higher is better \| \| `text_editing` \| 95.32 \| percent \| category \| Higher is better \| \| `rule_following` \| 63.79 \| percent \| category \| Higher is better \| \| `hallucination` \| 91.83 \| percent \| category \| Higher is better \| ### Configuration Reasoning effort unknown Model configuration Z.AI GLM 4.5 thinkingEnabled Not reported ### Source [Original source](https://www.nc-bench.com/models) Source nc bench Original model label Z.AI GLM 4.5 Observed 2026-10-22T06:10:03.426Z Evidence SHA-256 `ec261022458543624b08a136d01f5a2f0666cd52ffb49c64d6ca983e8543d1b5` Source locator `/rows/127` |  |  |  |  |  |  |
| [Longform Creative Writing](https://benchize.com/benchmarks/eq-bench%3Alongform-writing.md) | 55.5% | — | 64 / 93 | — | [eq bench · longform-writing](https://eqbench.com/creative_writing_longform.js) |  |
| ### Original source values \| Metric \| Value \| Unit \| Scope \| Direction \| \| --- \| --- \| --- \| --- \| --- \| \| `overall_score_100` \| 55.5 \| percent \| overall \| Higher is better \| \| `chapter1_avg` \| 13.50 \| rubric_score \| overall \| Higher is better \| \| `chapter2_avg` \| 12.80 \| rubric_score \| overall \| Higher is better \| \| `chapter3_avg` \| 12.33 \| rubric_score \| overall \| Higher is better \| \| `chapter4_avg` \| 12.22 \| rubric_score \| overall \| Higher is better \| \| `chapter5_avg` \| 12.26 \| rubric_score \| overall \| Higher is better \| \| `chapter6_avg` \| 11.67 \| rubric_score \| overall \| Higher is better \| \| `chapter7_avg` \| 11.73 \| rubric_score \| overall \| Higher is better \| \| `chapter8_avg` \| 12.31 \| rubric_score \| overall \| Higher is better \| \| `final_judgement_avg` \| 10.25 \| rubric_score \| overall \| Higher is better \| ### Configuration interactiveAdjustments none protocol longform-writing sourceModelVersion zai-org/GLM-4.5 ### Source [Original source](https://eqbench.com/creative_writing_longform.js) Source eq bench Original model label zai-org/GLM-4.5 Source version longform-writing Observed 2026-10-22T05:10:05.903Z Evidence SHA-256 `3ba283ce357ac7620e16db640a961879c30fe3ddc50a27de9a8ed4290784825c` Source locator `/leaderboardDataLongformV3/40` |  |  |  |  |  |  |
| [HMMT Feb 2025](https://benchize.com/benchmarks/matharena%3Ahmmt--hmmt_feb_2025.md) | 77.5% | 95% CI 70.03–84.97% | 13 / 35 | 0.06usd per problem | [matharena · hmmt--hmmt_feb_2025](https://matharena.ai/competition_tables/hmmt--hmmt_feb_2025) |  |
| ### Original source values \| Metric \| Value \| Unit \| Scope \| Direction \| \| --- \| --- \| --- \| --- \| --- \| \| `accuracy` \| 77.50 \| percent \| competition \| Higher is better \| \| `cost_per_problem` \| 0.056 \| usd_per_problem \| competition \| Lower is better \| ### Configuration competition hmmt--hmmt_feb_2025 predicted false sourceModelName GLM 4.5 sourceModelVersion glm/glm-45 ### Reported statistics Uncertainty 95% confidence interval: 70.03–84.97% confidenceInterval95 7.47 problems 30 ### Source [Original source](https://matharena.ai/competition_tables/hmmt--hmmt_feb_2025) Source matharena Original model label GLM 4.5 Source version hmmt--hmmt_feb_2025 Observed 2026-10-22T05:30:12.126Z Evidence SHA-256 `8554225c26eb7a3c2649943ee7cf6b404ec1f7441b20fbdcfccbf35b9a864864` Source locator `/table/rows/24` |  |  |  |  |  |  |

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Cite as: GLM-4.5 — Benchize, https://benchize.com/models/glm-4-5 (retrieved 2026-10-22)