GLM 5 vs Solar Pro 4
Updated October 21, 2026. 42 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick GLM 5 for coding: it scores 59.7 on the Vibe Coding Index against 24.4 for Solar Pro 4.
Pick Solar Pro 4 when output tokens cost 5.3x less, or when the context window is larger, 524K against 205K tokens.
- Shared results
- 42
- GLM 5 only
- 33
- Solar Pro 4 only
- 3
- Like-for-like categories
- 7 of 9
Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.
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.
Coding
Vibe Coding Index, four public coding benchmarks
GLM 5
GLM 5 scores 59.7 against 24.4.
2 and 1 benchmarks behind the scores
Intelligence
AA Intelligence Index
Solar Pro 4
Solar Pro 4 leads, 28.2 against 27.9.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only GLM 5 has a GPQA Diamond result, 83.3%.
Directional only
Math
AIME
No call
Only GLM 5 has a AIME result, 91.7%.
Directional only
Knowledge
MMLU Pro
No call
Only GLM 5 has a MMLU Pro result, 86.0%.
Directional only
Web design
Design Arena: websites
GLM 5
GLM 5 leads, 1247 against 1176.
Same board, both measured
Long documents
Listed context window
Solar Pro 4
Solar Pro 4 takes 524K tokens against 205K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Solar Pro 4
GLM 5 $0.0026, Solar Pro 4 $0.0004 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GLM 5 has the number, $0.63.
Directional only
At a glance
- Coding index
- GLM 5 59.7 from 2 benchmarks, Solar Pro 4 24.4 from 1 benchmark.
- Widest category
- General, 12.2 points apart on average over 18 shared benchmarks.
- Widest single gap
- LMArena Text: Polish: GLM 5 1434 against Solar Pro 4 1304, 21.5 points apart on a 0 to 100 scale.
- Output price
- GLM 5 $3.20 against Solar Pro 4 $0.60 per million output tokens, 5.3x apart.
- Context window
- GLM 5 takes 205K tokens, Solar Pro 4 524K.
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.
| Category | GLM 5 | Bars | Solar Pro 4 | Ties |
|---|---|---|---|---|
| Coding | 6 | 0 | ||
| Intelligence | 0 | 1 | ||
| Reasoning | 3 | 2 | ||
| Math | 2 | 0 | ||
| Knowledge | 4 | 0 | ||
| Web design | 6 | 0 | ||
| General | 18 | 0 | ||
| All shared boards | 39 | 3 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index60
| Benchmark | GLM 5 | Solar Pro 4 | Leader |
|---|---|---|---|
| SWE-bench Verified | 72.8% | Not measured | Only GLM 5 measured |
| SWE-bench Multilingual | 69.7% | Not measured | Only GLM 5 measured |
| LMArena WebDev | 1435 | 1371 | GLM 5 |
| AA Coding Index | Not measured | 52.7 | Only Solar Pro 4 measured |
| LiveCodeBench (Vals AI) | 81.9% | Not measured | Only GLM 5 measured |
| SWE-bench Verified (Vals AI) | 71.4% | Not measured | Only GLM 5 measured |
| Vibe Code Bench (Vals AI) | 23.4% | Not measured | Only GLM 5 measured |
| SciCode | Not measured | 48.0% | Only Solar Pro 4 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 43.2% | Not measured | Only GLM 5 measured |
| Terminal-Bench | 52.4% | Not measured | Only GLM 5 measured |
| WeirdML | 48.2% | Not measured | Only GLM 5 measured |
| ALE-Bench | 765.6 | 179.3 | GLM 5 |
| LMArena Text: coding | 1461 | 1438 | GLM 5 |
| LMArena Text: software and IT | 1460 | 1431 | GLM 5 |
| LMArena WebDev: React | 1424 | 1363 | GLM 5 |
| LMArena WebDev: HTML | 1450 | 1371 | GLM 5 |
| Neither model has a result on the other 22 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GLM 5 | Solar Pro 4 | Leader |
|---|---|---|---|
| AA Intelligence Index | 27.9 | 28.2 | Solar Pro 4 |
| Epoch Capabilities Index | 145.8 | Not measured | Only GLM 5 measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | GLM 5 | Solar Pro 4 | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | Not measured | 1105 | Only Solar Pro 4 measured |
| Design Arena: agents building full-stack apps | 1123 | Not measured | Only GLM 5 measured |
| Design Arena: agents building mobile apps | 1136 | Not measured | Only GLM 5 measured |
| Design Arena: agents building Android apps | 1152 | Not measured | Only GLM 5 measured |
| Design Arena: agents building Godot games | 1144 | Not measured | Only GLM 5 measured |
| Design Arena: HTML slides | 1148 | Not measured | Only GLM 5 measured |
| τ²-Bench Telecom | 98.2% | Not measured | Only GLM 5 measured |
| Vending-Bench 2 | $4,432 | Not measured | Only GLM 5 measured |
| Neither model has a result on the other 31 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index32
| Benchmark | GLM 5 | Solar Pro 4 | Leader |
|---|---|---|---|
| GPQA Diamond | 83.3% | Not measured | Only GLM 5 measured |
| GPQA Diamond (Artificial Analysis run) | 82.0% | 89.1% | Solar Pro 4 |
| Humanity's Last Exam (Artificial Analysis run) | 29.3% | 29.8% | Solar Pro 4 |
| GPQA Diamond (Epoch AI run) | 87.8% | Not measured | Only GLM 5 measured |
| ARC-AGI | 44.7% | Not measured | Only GLM 5 measured |
| ARC-AGI-2 | 4.9% | Not measured | Only GLM 5 measured |
| SimpleBench | 53.2% | Not measured | Only GLM 5 measured |
| LMArena Text: hard prompts | 1452 | 1400 | GLM 5 |
| LMArena Text: expert | 1454 | 1428 | GLM 5 |
| LMArena Text: hard prompts in English | 1460 | 1427 | GLM 5 |
| Neither model has a result on the other 11 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GLM 5 | Solar Pro 4 | Leader |
|---|---|---|---|
| AIME | 91.7% | Not measured | Only GLM 5 measured |
| OTIS Mock AIME | 80.0% | Not measured | Only GLM 5 measured |
| LMArena Text: math | 1440 | 1421 | GLM 5 |
| LMArena Text: mathematical work | 1451 | 1427 | GLM 5 |
| Neither model has a result on the other 9 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | GLM 5 | Solar Pro 4 | Leader |
|---|---|---|---|
| MMLU Pro | 86.0% | Not measured | Only GLM 5 measured |
| LegalBench (Vals AI) | 84.1% | Not measured | Only GLM 5 measured |
| CaseLaw (Vals AI) | 52.5% | Not measured | Only GLM 5 measured |
| CorpFin (Vals AI) | 62.9% | Not measured | Only GLM 5 measured |
| TaxEval (Vals AI) | 70.0% | Not measured | Only GLM 5 measured |
| MedQA (Vals AI) | 94.3% | Not measured | Only GLM 5 measured |
| LMArena Text: science | 1460 | 1404 | GLM 5 |
| LMArena Text: medicine and healthcare | 1455 | 1374 | GLM 5 |
| LMArena Text: legal and government | 1453 | 1383 | GLM 5 |
| LMArena Text: business and finance | 1430 | 1381 | GLM 5 |
| Neither model has a result on the other 7 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index60
| Benchmark | GLM 5 | Solar Pro 4 | Leader |
|---|---|---|---|
| Design Arena: websites | 1247 | 1176 | GLM 5 |
| Design Arena: UI components | 1230 | 1150 | GLM 5 |
| Design Arena: game dev | 1234 | 1170 | GLM 5 |
| Design Arena: data viz | 1228 | 1177 | GLM 5 |
| Design Arena: 3D | 1229 | 1178 | GLM 5 |
| Design Arena: all code categories | 1246 | 1182 | GLM 5 |
| Design Arena: SVG | 1168 | Not measured | Only GLM 5 measured |
| Design Arena: ASCII art | 1146 | Not measured | Only GLM 5 measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index180
| Benchmark | GLM 5 | Solar Pro 4 | Leader |
|---|---|---|---|
| IFBench | 72.3% | Not measured | Only GLM 5 measured |
| Long context reasoning (AA-LCR) | 75.7% | 70.7% | GLM 5 |
| CL-bench | 18.7% | Not measured | Only GLM 5 measured |
| LMArena Text | 1446 | 1388 | GLM 5 |
| LMArena Text: instruction following | 1428 | 1375 | GLM 5 |
| LMArena Text: creative writing | 1438 | 1317 | GLM 5 |
| LMArena Text: English | 1458 | 1414 | GLM 5 |
| LMArena Text: non-English | 1430 | 1363 | GLM 5 |
| LMArena Text: Chinese | 1511 | 1422 | GLM 5 |
| LMArena Text: German | 1447 | 1358 | GLM 5 |
| LMArena Text: Japanese | 1416 | 1320 | GLM 5 |
| LMArena Text: Korean | 1423 | 1383 | GLM 5 |
| LMArena Text: French | 1456 | 1400 | GLM 5 |
| LMArena Text: Spanish | 1454 | 1409 | GLM 5 |
| LMArena Text: Russian | 1436 | 1357 | GLM 5 |
| LMArena Text: Polish | 1434 | 1304 | GLM 5 |
| LMArena Text: multi-turn | 1456 | 1385 | GLM 5 |
| LMArena Text: longer queries | 1446 | 1382 | GLM 5 |
| LMArena Text: writing and language | 1437 | 1344 | GLM 5 |
| LMArena Text: entertainment and media | 1426 | 1332 | GLM 5 |
| Neither model has a result on the other 26 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GLM 5 | Solar Pro 4 | Leader |
|---|---|---|---|
| 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
Solar Pro 4 costs less
Repository review
50K input + 3K output tokens
Solar Pro 4 costs less
Agent loop
200K input + 10K output tokens
Solar Pro 4 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.
| Specification | Z.ai GLM 5 | Upstage Solar Pro 4 |
|---|---|---|
| Maker | Z.ai | Upstage |
| Weights | Open weights | No public weights listed |
| Released | February 11, 2026 | August 10, 2026 |
| Context window | 205K | 524K |
| Input $/Mtok | $1.00 | $0.15 |
| Output $/Mtok | $3.20 | $0.60 |
| Coding index | 59.7 | 24.4 |
| Independent measurements behind it | 2 | 1 |
| Cost per solved task | $0.63 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GLM 5 better than Solar Pro 4 for coding?
Pick GLM 5 for coding: it scores 59.7 on the Vibe Coding Index against 24.4 for Solar Pro 4. Pick Solar Pro 4 when output tokens cost 5.3x less, or when the context window is larger, 524K against 205K tokens.
Which is cheaper, GLM 5 or Solar Pro 4?
GLM 5 costs $1.00 per million input tokens and $3.20 per million output tokens; Solar Pro 4 costs $0.15 and $0.60. Cost per solved task is known for GLM 5 only.
Which has the bigger context window, GLM 5 or Solar Pro 4?
Solar Pro 4, with 524K tokens against 205K.
How many benchmarks is the GLM 5 vs Solar Pro 4 comparison based on?
42 benchmarks have a result for both models as of October 21, 2026. GLM 5's coding index rests on 2 independent benchmarks and Solar Pro 4's on 1. Where only one model has a result, the page says so instead of naming a winner.