GLM 5.3 · Data analysis
GLM 5.3 for data analysis: our test runs
GLM 5.3 ran our 5 data analysis prompts in llmwise, through the same pipeline your messages take. Here's every reply as it came, whether it passed, what it cost and what it counts as on Pro, next to the other models.
Based on 5 of our test runs on , through OpenRouter with the app's own prompt and settings. Updated .
Short answer
In our test runs on September 27, 2026, GLM 5.3 passed 5 of 5 of our data analysis prompts (both hard ones): tied 1st of 20 models. Each reply counted as 1 message on Pro, where it has 250 a month, and cost $0.0019 to run on average.
Prompt by prompt
Each of the 5 data analysis prompts, and how GLM 5.3's reply did.
| Prompt | Result | Cost | Time |
|---|---|---|---|
| The region with the most revenueEveryday | Passed: Final answer North, 1,085.00: right. | $0.0004 | 2.1 s |
| Average order value in AugustEveryday | Passed: Final answer 300.00: right. | $0.0004 | 1.9 s |
| Revenue change from July to AugustEveryday | Passed: Final answer 67.4%: right. | $0.0016 | 1.4 s |
| A median, filtered two waysHard | Passed: Final answer 6.25: right. | $0.0011 | 1.0 s |
| Correlation between ad spend and sign-upsHard | Passed: Final answer 0.97: right. | $0.0062 | 5.6 s |
Every data analysis reply from GLM 5.3
The region with the most revenue
An everyday prompt: “The region with the most revenue”, in full.
Passed: Final answer North, 1,085.00: right.
**West:** - 1001: 2×45 = 90 - 1003: 1×310 = 310 - 1007: 2×120 = 240 - 1010: 5×45 = 225 - Total: 865 **East:** - 1002: 120 - 1005: 3×45 = 135 - 1008: 310 - 1011: 3×120 = 360 - Total: 925 **North:** - 1004: 4×45 = 180 - 1006: 2×120 = 240 - 1009: 2×310 = 620 - 1012: 45 - Total: 1085 Final answer: North, $1,085.00
654 tokens in, 189 out · 2.1 s · $0.0004 · 1 message on Pro · answered by z-ai/glm-5.3 via Baidu ·
Average order value in August
An everyday prompt: “Average order value in August”, in full.
Passed: Final answer 300.00: right.
August 2026 orders and revenue (quantity × price): - 1007: 2 × 120 = 240.00 - 1008: 1 × 310 = 310.00 - 1009: 2 × 310 = 620.00 - 1010: 5 × 45 = 225.00 - 1011: 3 × 120 = 360.00 - 1012: 1 × 45 = 45.00 Total = 240 + 310 + 620 + 225 + 360 + 45 = 1800.00 Orders = 6 Average = 1800 / 6 = 300.00 Final answer: 300.00
661 tokens in, 164 out · 1.9 s · $0.0004 · 1 message on Pro · answered by z-ai/glm-5.3 via Baidu ·
Revenue change from July to August
An everyday prompt: “Revenue change from July to August”, in full.
Passed: Final answer 67.4%: right.
**July 2026 revenue:** - 2×45=90, 1×120=120, 1×310=310, 4×45=180, 3×45=135, 2×120=240 → **$1,075** **August 2026 revenue:** - 2×120=240, 1×310=310, 2×310=620, 5×45=225, 3×120=360, 1×45=45 → **$1,800** **Change:** (1800 − 1075) / 1075 = 725/1075 ≈ 0.6744 Final answer: 67.4%
690 tokens in, 218 out (62 of them reasoning) · 1.4 s · $0.0016 · 1 message on Pro · answered by z-ai/glm-5.3 via Wafer ·
A median, filtered two ways
A hard prompt: “A median, filtered two ways”, in full.
Passed: Final answer 6.25: right.
Billing high-priority tickets: 5.5, 2, 9, 7, 26, 4 (six values). Sorted: 2, 4, 5.5, 7, 9, 26. With an even count, the median is the average of the two middle values: (5.5 + 7) / 2 = 6.25. Final answer: 6.25
549 tokens in, 149 out (57 of them reasoning) · 1.0 s · $0.0011 · 1 message on Pro · answered by z-ai/glm-5.3 via Wafer ·
Correlation between ad spend and sign-ups
A hard prompt: “Correlation between ad spend and sign-ups”, in full.
Passed: Final answer 0.97: right.
**Working:** - n = 8; mean ad_spend = 768.75, mean signups = 54.25 - Σ(x−x̄)(y−ȳ) = 23,912.5 - Σ(x−x̄)² = 624,687.5; Σ(y−ȳ)² = 971.5 - r = 23,912.5 / √(624,687.5 × 971.5) = 23,912.5 / 24,635 ≈ 0.9707 Final answer: 0.97
491 tokens in, 1,336 out (1,196 of them reasoning) · 5.6 s · $0.0062 · 1 message on Pro · answered by z-ai/glm-5.3 via Wafer ·
How it compares on data analysis
GLM 5.3 beside the job's picks among every model. 16 models share the hard-problems pick, GLM 5.3 among them.
| Model | Passed | On Pro | Cost per reply |
|---|---|---|---|
| GLM 5.3Our pick: hard problems (shared), best value | 5 of 5 | 250 a month on Pro | $0.0019 |
| GPT-6 LunaOur pick: hard problems (shared), everyday | 5 of 5 | 60 a day on Pro | $0.0002 |
Every limit is published. Paid plans also have a monthly fair-use limit on AI cost: Plus $3.75, Pro $7.50, Max $20, Ultra $42, Studio $85. Using every message on your plan at typical sizes stays under it; very large messages and heavy research use it faster. Every limit, explained.
GLM 5.3 next to each model on data analysis
GLM 5.3 against each model on the same 5 data analysis prompts. One run each, through OpenRouter: a wait depends on the provider and the load that day, so a lead under 10% counts as close.
Against Claude Fable 5.1: GLM 5.3 answered 2.5× sooner (1.9 s to 4.9 s), cost 14.8× less, and passed 5 of 5 to its 5.
Against Claude Opus 5.5: GLM 5.3 answered 2.4× sooner (1.9 s to 4.6 s), cost 6.8× less, and passed 5 of 5 to its 5.
Against Claude Sonnet 5.5: GLM 5.3 answered 1.2× sooner (1.9 s to 2.3 s), cost 2.5× less, and passed 5 of 5 to its 5.
Against Claude Sonnet 5: GLM 5.3 answered 2.7× sooner (1.9 s to 5.3 s), cost 3.6× less, and passed 5 of 5 to its 4. Only GLM 5.3 passed Correlation between ad spend and sign-ups.
Against Claude Haiku 5.5: GLM 5.3 answered 1.7× sooner (1.9 s to 3.3 s), cost 5.3× more, and passed 5 of 5 to its 5.
Against Claude Haiku 4.5: GLM 5.3 answered 1.4× sooner (1.9 s to 2.7 s), cost 1.3× less, and passed 5 of 5 to its 3. Only GLM 5.3 passed Average order value in August; Correlation between ad spend and sign-ups.
Against GPT-6 Astra: GLM 5.3 answered 1.7× sooner (1.9 s to 3.3 s), cost 8.1× less, and passed 5 of 5 to its 5.
Against GPT-6.1 Sol: GLM 5.3 answered 1.5× sooner (1.9 s to 3.0 s), cost 1.2× more, and passed 5 of 5 to its 5.
Against GPT-6 Sol: GLM 5.3 answered 1.4× sooner (1.9 s to 2.8 s), cost 1.8× less, and passed 5 of 5 to its 5.
Against GPT-6 Luna: GLM 5.3 answered 1.3× sooner (1.9 s to 2.5 s), cost 10.9× more, and passed 5 of 5 to its 5.
Against Gemini 4 Argon: GLM 5.3 answered 3.5× sooner (1.9 s to 6.9 s), cost 1.5× less, and passed 5 of 5 to its 5.
Against Gemini 3.1 Pro (preview): GLM 5.3 answered 4.5× sooner (1.9 s to 8.6 s), cost 8.1× less, and passed 5 of 5 to its 5.
Against Gemini 3.8 Flash: GLM 5.3 answered 2.8× sooner (1.9 s to 5.4 s), cost 1.4× less, and passed 5 of 5 to its 4. Only GLM 5.3 passed Correlation between ad spend and sign-ups.
Against DeepSeek V4.1 Flash: GLM 5.3 answered 2.2× later (1.9 s to 0.9 s), cost 2.3× more, and passed 5 of 5 to its 5.
Against DeepSeek V4 Pro: GLM 5.3 answered 2.1× sooner (1.9 s to 4.1 s), cost 1.5× less, and passed 5 of 5 to its 5.
Against Grok 4.7: GLM 5.3 answered 4.6× sooner (1.9 s to 8.9 s), cost 5.8× less, and passed 5 of 5 to its 5.
Against Kimi K3: GLM 5.3 answered 1.8× sooner (1.9 s to 3.5 s), cost 3.5× less, and passed 5 of 5 to its 5.
Against GLM 5.3 Flash: GLM 5.3 answered 5.1× sooner (1.9 s to 9.8 s), cost 5.0× more, and passed 5 of 5 to its 4. Only GLM 5.3 passed Correlation between ad spend and sign-ups.
Against Mistral Large 4: GLM 5.3 answered 8.2× sooner (1.9 s to 15.8 s), cost 1.9× less, and passed 5 of 5 to its 5.
How these runs were done
Final answer. Automatic. The reply's last “Final answer:” line must hold the right value.
GLM 5.3, and data analysis, elsewhere
- GLM 5.3: price, limits and messages on every plan
- GLM 5.3 for coding: our test runs
- GLM 5.3 for writing: our test runs
- GLM 5.3 for math: our test runs
- GLM 5.3 vs GLM 5.3 Flash
- Kimi K3 vs GLM 5.3
- DeepSeek V4 Pro vs GLM 5.3
- Claude Sonnet 5 vs GLM 5.3
- Claude Haiku 4.5 vs GLM 5.3
- GPT-6 Sol vs GLM 5.3
- GPT-6 Luna vs GLM 5.3
- Gemini 3.1 Pro (preview) vs GLM 5.3
- Gemini 3.8 Flash vs GLM 5.3
- DeepSeek V4.1 Flash vs GLM 5.3
- Grok 4.7 vs GLM 5.3
- Analyze a CSV with code: the prompt, and its price
- AI prompts for business, tested on four models
- Our test runs: 50 prompts on every model
Questions
Is GLM 5.3 good for data analysis?
In our test runs it passed 5 of 5 data analysis prompts, tied 1st of the 20 models in llmwise. Every reply is on this page, so you can judge them yourself.
How many of my messages does a data analysis reply from GLM 5.3 use?
1 message each on Pro, where it has 250 a month on Pro. The price of a message is fixed and shown before you send it, however long the reply.
How were these runs done?
The same way for every model: each prompt sent through llmwise's own pipeline, each reply checked the same way. The methods page has every prompt and how each is scored.
Claude, GPT, Gemini, DeepSeek, Grok, Kimi, GLM, and Mistral, in one chat.
See what a message costs before you send it. Free is 5 messages to try; sign in with an email link, no password or card.