Data points: 198
Model compare
The readout for DeepSeek V4 Pro and GLM-5.2, before the detailed comparison sheet.
Weighted outcome: GLM-5.2. Benchmark capability categories carry 80%, while price, API performance, and availability carry 20%.
Decision read
GLM-5.2
GLM-5.2 has the higher weighted result; Model A / B score 8 to 92.
Evidence depth
198 data points
Includes 46 benchmark rows, 6 audit samples, and 7 provider examples.
Selection signal
Start with GLM-5.2
The charts below split 59 high-signal samples across speed, scores, and audit health.
Switch either side of this report to compare another model with the same LMSpeed data pipeline.
Select a different model to open a new comparison URL.
This report only uses LMSpeed data for DeepSeek V4 Pro and GLM-5.2: pricing, speed aggregates, third-party benchmark scores, and shared provider samples.
| Model compare | DeepSeek V4 Pro | GLM-5.2 |
|---|---|---|
| Overall leader | Contender | Leading |
| Weighted overall score | 8.0 pts | 92.0 pts |
| Benchmark category leads | 0 categories | 6 categories |
| Operational advantages | Free providers, Provider coverage | Cheapest input price, Average speed, First-token latency |
| Context window | 1.0M tokens | 1.0M tokens |
| Max output | 384K tokens | 131.1K tokens |
| Modalities | Input Text Output Text | Input Text Output Text |
| Features | Text inputText outputTool callingStructured outputsJSON modeReasoning | Text inputText outputTool callingStructured outputsJSON modeReasoning |
The overall result weights benchmark capability categories at 80% and price, API speed/latency, and availability at 20%. Recent test volume does not affect the winner, and missing benchmark categories are excluded.
| Model compare | DeepSeek V4 Pro | GLM-5.2 |
|---|---|---|
| Developer | DeepSeek | Z.ai |
| Released | Apr 2026 | Jun 2026 |
| Parameters | No data | No data |
| Tokenizer | DeepSeek | Other |
| Knowledge cutoff | No data | No data |
| OpenRouter ID | deepseek/deepseek-v4-pro | z-ai/glm-5.2 |
| References | No data | No data |
This report only uses LMSpeed data for DeepSeek V4 Pro and GLM-5.2: pricing, speed aggregates, third-party benchmark scores, and shared provider samples.
DeepSeek V4 Pro
DeepSeek V4 Pro has these operational advantages: Free providers, Provider coverage.
GLM-5.2
GLM-5.2 is stronger in benchmark categories (Agents, Coding, Reasoning, Knowledge, Math) and operational dimensions (Cheapest input price, Average speed, First-token latency).
Third-party benchmark profile synced into LMSpeed; only metrics available for both models are shown.
Compare benchmark category scores on a 0-100 scale. Select a category to inspect the gap.
Avg. score
DeepSeek V4 Pro
47.7
Avg. score
GLM-5.2
59.1
GLM-5.2 leads by 9.2
GLM-5.2 leads by 7.3
GLM-5.2 leads by 1.1
GLM-5.2 leads by 15.0
GLM-5.2 leads by 34.7
No data
No data
GLM-5.2 leads by 0.7
Metric-level scores with benchmark source, rank depth, confidence, error, and evaluation date where available.
DeepSeek V4 Pro
65.0
Rank #24/91 · confidence 2 · eval date 2026-04-24
GLM-5.2
winner70.0
Rank #16/91 · confidence 2 · eval date 2026-06-16
DeepSeek V4 Pro
56.1 tok/s
Rank #53/71 · confidence 4
GLM-5.2
winner139.3 tok/s
Rank #20/71 · confidence 4
DeepSeek V4 Pro
1.04 s
Rank #32/71 · confidence 4
GLM-5.2
winner0.96 s
Rank #27/71 · confidence 4
DeepSeek V4 Pro
36.58 s
Rank #55/71 · confidence 4
GLM-5.2
winner15.32 s
Rank #40/71 · confidence 4
DeepSeek V4 Pro
winner$0.870/M
Rank #35/170 · confidence 4
GLM-5.2
$4.40/M
Rank #103/170 · confidence 4
DeepSeek V4 Pro
winner$0.544/M
Rank #50/170 · confidence 4
GLM-5.2
$2.15/M
Rank #110/170 · confidence 4
DeepSeek V4 Pro
winner$0.435/M
Rank #70/170 · confidence 4
GLM-5.2
$1.40/M
Rank #122/170 · confidence 4
DeepSeek V4 Pro
12.9
Rank #20/78 · confidence 2 · eval date 2026-04-24
GLM-5.2
winner20.9
Rank #10/78 · confidence 2 · eval date 2026-06-16
DeepSeek V4 Pro
33.5%
Rank #27/194 · confidence 4
GLM-5.2
winner40.1%
Rank #14/194 · confidence 4
DeepSeek V4 Pro
66.3
Rank #41/94 · confidence 2 · eval date 2026-04-24
GLM-5.2
winner71.3
Rank #15/94 · confidence 2 · eval date 2026-06-16
DeepSeek V4 Pro
winner90.5%
Rank #20/195 · confidence 4
GLM-5.2
89.5%
Rank #28/195 · confidence 4
DeepSeek V4 Pro
46.2
Rank #7/13 · confidence 2 · eval date 2026-04-24
GLM-5.2
winner50.8
Rank #5/13 · confidence 2 · eval date 2026-06-16
DeepSeek V4 Pro
67.9
Rank #17/31 · confidence 2 · eval date 2026-04-24
GLM-5.2
winner81.0
Rank #7/31 · confidence 2 · eval date 2026-06-16
DeepSeek V4 Pro
64.0
Rank #16/17 · confidence 2 · eval date 2026-04-24
GLM-5.2
winner77.9
Rank #10/17 · confidence 2 · eval date 2026-06-16
DeepSeek V4 Pro
55.4
Rank #30/43 · confidence 2 · eval date 2026-04-24
GLM-5.2
winner62.1
Rank #10/43 · confidence 2 · eval date 2026-06-16
DeepSeek V4 Pro
59.4
Rank #22/64 · confidence 2 · eval date 2026-04-24
GLM-5.2
winner68.8
Rank #17/64 · confidence 2 · eval date 2026-06-16
DeepSeek V4 Pro
46.4%
Rank #35/192 · confidence 4
GLM-5.2
winner50.5%
Rank #18/192 · confidence 4
DeepSeek V4 Pro
50.0
Rank #25/101 · confidence 2 · eval date 2026-04-24
GLM-5.2
winner50.5
Rank #22/101 · confidence 2 · eval date 2026-06-16
DeepSeek V4 Pro
winner50.6
Rank #42/72 · confidence 2 · eval date 2026-04-24
GLM-5.2
50.4
Rank #43/72 · confidence 2 · eval date 2026-06-16
DeepSeek V4 Pro
winner95.2
Rank #2/15 · confidence 2 · eval date 2026-04-24
GLM-5.2
92.5
Rank #6/15 · confidence 2 · eval date 2026-06-16
DeepSeek V4 Pro
winner82.0
Rank #4/58 · confidence 2 · eval date 2026-04-24
GLM-5.2
81.4
Rank #7/58 · confidence 2 · eval date 2026-06-16
DeepSeek V4 Pro
winner50.0
Rank #1/9 · confidence 2 · eval date 2026-04-24
GLM-5.2
44.4
Rank #3/9 · confidence 2 · eval date 2026-06-16
DeepSeek V4 Pro
winner94.0
Rank #4/95 · confidence 2 · eval date 2026-04-24
GLM-5.2
28.1
Rank #89/95 · confidence 2 · eval date 2026-06-16
DeepSeek V4 Pro
71.8
Rank #26/61 · confidence 2 · eval date 2026-04-24
GLM-5.2
winner82.4
Rank #11/61 · confidence 2 · eval date 2026-06-16
DeepSeek V4 Pro
90.1
Rank #15/26 · confidence 2 · eval date 2026-04-24
GLM-5.2
winner91.2
Rank #12/26 · confidence 2 · eval date 2026-06-16
DeepSeek V4 Pro
35.9
Rank #22/101 · confidence 2 · eval date 2026-04-24
GLM-5.2
winner40.1
Rank #13/101 · confidence 2 · eval date 2026-06-16
DeepSeek V4 Pro
44.3
Rank #20/104 · confidence 2 · eval date 2026-04-24
GLM-5.2
winner51.1
Rank #13/104 · confidence 2 · eval date 2026-06-16
DeepSeek V4 Pro
winner43.3
Rank #20/95 · confidence 2 · eval date 2026-04-24
GLM-5.2
25.1
Rank #62/95 · confidence 2 · eval date 2026-06-16
DeepSeek V4 Pro
88.8
Rank #32/101 · confidence 2 · eval date 2026-04-24
GLM-5.2
winner89.5
Rank #29/101 · confidence 2 · eval date 2026-06-16
DeepSeek V4 Pro
1260.0
Rank #31/69 · confidence 2 · eval date 2026-04-24
GLM-5.2
winner1341.0
Rank #2/69 · confidence 2 · eval date 2026-06-16
DeepSeek V4 Pro
winner76.5
Rank #12/86 · confidence 2 · eval date 2026-04-24
GLM-5.2
73.3
Rank #26/86 · confidence 2 · eval date 2026-06-16
DeepSeek V4 Pro
96.2
Rank #12/84 · confidence 2 · eval date 2026-04-24
GLM-5.2
winner99.1
Rank #1/84 · confidence 2 · eval date 2026-06-16
DeepSeek V4 Pro
17.1
Rank #11/19 · confidence 2 · eval date 2026-04-24
GLM-5.2
winner20.7
Rank #2/19 · confidence 2 · eval date 2026-06-16
DeepSeek V4 Pro
84.4
Rank #12/17 · confidence 2 · eval date 2026-04-24
GLM-5.2
winner91.0
Rank #6/17 · confidence 2 · eval date 2026-06-16
DeepSeek V4 Pro
38.3
Rank #9/12 · confidence 2 · eval date 2026-04-24
GLM-5.2
winner42.7
Rank #6/12 · confidence 2 · eval date 2026-06-16
DeepSeek V4 Pro
24.3
Rank #13/24 · confidence 2 · eval date 2026-04-24
GLM-5.2
winner33.7
Rank #6/24 · confidence 2 · eval date 2026-06-16
DeepSeek V4 Pro
930.0
Rank #11/18 · confidence 2 · eval date 2026-04-24
GLM-5.2
winner1254.0
Rank #8/18 · confidence 2 · eval date 2026-06-16
DeepSeek V4 Pro
73.6
Rank #14/27 · confidence 2 · eval date 2026-04-24
GLM-5.2
winner76.8
Rank #8/27 · confidence 2 · eval date 2026-06-16
DeepSeek V4 Pro
67.9
Rank #20/51 · confidence 2 · eval date 2026-04-24
GLM-5.2
winner81.0
Rank #8/51 · confidence 2 · eval date 2026-06-16
DeepSeek V4 Pro
25.8
Rank #11/17 · confidence 2 · eval date 2026-04-24
GLM-5.2
winner26.8
Rank #9/17 · confidence 2 · eval date 2026-06-16
DeepSeek V4 Pro
winner51.8
Rank #9/22 · confidence 2 · eval date 2026-04-24
GLM-5.2
48.2
Rank #12/22 · confidence 2 · eval date 2026-06-16
DeepSeek V4 Pro
40.4
Rank #12/17 · confidence 2 · eval date 2026-04-24
GLM-5.2
winner42.7
Rank #10/17 · confidence 2 · eval date 2026-06-16
DeepSeek V4 Pro
1306.0
Rank #18/60 · confidence 2 · eval date 2026-04-24
GLM-5.2
winner1510.0
Rank #10/60 · confidence 2 · eval date 2026-06-16
DeepSeek V4 Pro
40.3
Rank #18/55 · confidence 2 · eval date 2026-04-24
GLM-5.2
winner50.5
Rank #10/55 · confidence 2 · eval date 2026-06-16
DeepSeek V4 Pro
36.4
Rank #17/60 · confidence 2 · eval date 2026-04-24
GLM-5.2
winner43.1
Rank #12/60 · confidence 2 · eval date 2026-06-16
DeepSeek V4 Pro
67.4
Rank #22/60 · confidence 2 · eval date 2026-04-24
GLM-5.2
winner81.0
Rank #15/60 · confidence 2 · eval date 2026-06-16
Latest completed audits from shared providers, with four safety and integrity score groups plus report links.
| Provider | DeepSeek V4 Pro | GLM-5.2 |
|---|---|---|
Xinjianya APIWinner: GLM-5.2 | DeepSeek V4 Pro deepseek-ai/deepseek-v4-pro Audit score 81 727280100 | GLM-5.2 z-ai/glm-5.2 Audit score 96 10084100100 |
小水管 APIWinner: DeepSeek V4 Pro | DeepSeek V4 Pro deepseek-v4-pro Audit score 87 788486100 | GLM-5.2 glm-5.2-202k Audit score 81 727280100 |
Tokeness.ioWinner: GLM-5.2 | DeepSeek V4 Pro deepseek-v4-pro No audit yet | GLM-5.2 glm-5.2 Audit score 83 668480100 |
小老鼠的奶酪工坊-酒馆聊天apiWinner: GLM-5.2 | DeepSeek V4 Pro deepseek-v4-pro No audit yet | GLM-5.2 glm-5.2 Audit score 82 727580100 |
9527 APIWinner: DeepSeek V4 Pro | DeepSeek V4 Pro deepseek-v4-pro Audit score 77 70728084 | GLM-5.2 glm-5.2 No audit yet |
MyDamoxingWinner: GLM-5.2 | DeepSeek V4 Pro deepseek-v4-pro No audit yet | GLM-5.2 GLM-5.2-C Audit score 75 597863100 |
Speed aggregates and input/output pricing share each provider row for real API selection and migration cost checks.
| Provider | DeepSeek V4 Pro | GLM-5.2 |
|---|---|---|
NVIDIA NIM70 tests | DeepSeek V4 Pro speed / latency 22 tok/s / 2343ms input / output No data | GLM-5.2 speed / latency 49 tok/s / 1704ms input / output No data |
Ollama60 tests | DeepSeek V4 Pro speed / latency N/A / N/A input / output No data | GLM-5.2 speed / latency 91 tok/s / 6210ms input / output No data |
火山引擎 Ark35 tests | DeepSeek V4 Pro speed / latency 46 tok/s / 5962ms input / output No data | GLM-5.2 speed / latency 48 tok/s / 7975ms input / output No data |
天云港模型开放平台20 tests | DeepSeek V4 Pro speed / latency 35 tok/s / 11460ms input / output No data | GLM-5.2 speed / latency 47 tok/s / 15698ms input / output No data |
OpenCode15 tests | DeepSeek V4 Pro speed / latency 53 tok/s / 13840ms input / output No data | GLM-5.2 speed / latency 62 tok/s / 8564ms input / output No data |
DeepSeek V4 Pro deepseek-ai/deepseek-v4-pro speed / latency No data input / output $0/request | GLM-5.2 glm-5.2 speed / latency No data input / output $0.200/request | |
DeepSeek V4 Pro deepseek-v4-pro speed / latency No data input / output $0.143/M/$0.286/M | GLM-5.2 glm-5.2 speed / latency No data input / output $0/M/$0/M |
Weighted outcome: GLM-5.2. Benchmark capability categories carry 80%, while price, API performance, and availability carry 20%.
