GPT-5.1-Codex vs Solar Pro 4
Updated October 21, 2026. 13 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick GPT-5.1-Codex for coding: it scores 50.5 on the Vibe Coding Index against 24.4 for Solar Pro 4.
Pick Solar Pro 4 when output tokens cost 16.7x less, or when the context window is larger, 524K against 400K tokens.
- Shared results
- 13
- GPT-5.1-Codex only
- 13
- Solar Pro 4 only
- 32
- Like-for-like categories
- 6 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
GPT-5.1-Codex
GPT-5.1-Codex scores 50.5 against 24.4.
2 and 1 benchmarks behind the scores
Intelligence
AA Intelligence Index
Solar Pro 4
Solar Pro 4 leads, 28.2 against 23.7.
Same board, both measured
Web design
Design Arena: websites
Solar Pro 4
Solar Pro 4 leads, 1176 against 1162.
Same board, both measured
Long documents
Listed context window
Solar Pro 4
Solar Pro 4 takes 524K tokens against 400K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Solar Pro 4
GPT-5.1-Codex $0.0063, Solar Pro 4 $0.0004 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-5.1-Codex has the number, $0.892.
Directional only
At a glance
- Coding index
- GPT-5.1-Codex 50.5 from 2 benchmarks, Solar Pro 4 24.4 from 1 benchmark.
- Widest category
- Coding, 14.8 points apart on average over 3 shared benchmarks.
- Widest single gap
- ALE-Bench: GPT-5.1-Codex 1244.9 against Solar Pro 4 179.3, 35.5 points apart on a 0 to 100 scale.
- Output price
- GPT-5.1-Codex $10.00 against Solar Pro 4 $0.60 per million output tokens, 16.7x apart.
- Context window
- GPT-5.1-Codex takes 400K 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 | GPT-5.1-Codex | Bars | Solar Pro 4 | Ties |
|---|---|---|---|---|
| Coding | 1 | 2 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 0 | 2 | ||
| Web design | 2 | 3 | ||
| General | 0 | 1 | ||
| All shared boards | 3 | 10 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index12
| Benchmark | GPT-5.1-Codex | Solar Pro 4 | Leader |
|---|---|---|---|
| SWE-bench Verified | 66.0% | Not measured | Only GPT-5.1-Codex measured |
| LMArena WebDev | 1337 | 1371 | Solar Pro 4 |
| AA Coding Index | Not measured | 52.7 | Only Solar Pro 4 measured |
| LiveCodeBench (Vals AI) | 85.5% | Not measured | Only GPT-5.1-Codex measured |
| Vibe Code Bench (Vals AI) | 13.1% | Not measured | Only GPT-5.1-Codex measured |
| LiveCodeBench (Artificial Analysis run) | 84.9% | Not measured | Only GPT-5.1-Codex measured |
| SciCode | Not measured | 48.0% | Only Solar Pro 4 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 34.8% | Not measured | Only GPT-5.1-Codex measured |
| Terminal-Bench | 57.8% | Not measured | Only GPT-5.1-Codex measured |
| ALE-Bench | 1244.9 | 179.3 | GPT-5.1-Codex |
| LMArena Text: coding | Not measured | 1438 | Only Solar Pro 4 measured |
| LMArena Text: software and IT | Not measured | 1431 | Only Solar Pro 4 measured |
| LMArena WebDev: React | Not measured | 1363 | Only Solar Pro 4 measured |
| LMArena WebDev: HTML | 1346 | 1371 | Solar Pro 4 |
| Neither model has a result on the other 24 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-5.1-Codex | Solar Pro 4 | Leader |
|---|---|---|---|
| AA Intelligence Index | 23.7 | 28.2 | Solar Pro 4 |
| Neither model has a result on the other 1 board here | |||
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-5.1-Codex | Solar Pro 4 | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | 1018 | 1105 | Solar Pro 4 |
| Design Arena: agents building full-stack apps | 1086 | Not measured | Only GPT-5.1-Codex measured |
| Design Arena: agents building mobile apps | 1191 | Not measured | Only GPT-5.1-Codex measured |
| τ²-Bench Telecom | 83.0% | Not measured | Only GPT-5.1-Codex measured |
| Neither model has a result on the other 35 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | GPT-5.1-Codex | Solar Pro 4 | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 86.0% | 89.1% | Solar Pro 4 |
| Humanity's Last Exam (Artificial Analysis run) | 25.7% | 29.8% | Solar Pro 4 |
| LMArena Text: hard prompts | Not measured | 1400 | Only Solar Pro 4 measured |
| LMArena Text: expert | Not measured | 1428 | Only Solar Pro 4 measured |
| LMArena Text: hard prompts in English | Not measured | 1427 | Only Solar Pro 4 measured |
| Neither model has a result on the other 16 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | GPT-5.1-Codex | Solar Pro 4 | Leader |
|---|---|---|---|
| AA Math Index | 95.7 | Not measured | Only GPT-5.1-Codex measured |
| AIME 2025 (Artificial Analysis run) | 95.7% | Not measured | Only GPT-5.1-Codex measured |
| LMArena Text: math | Not measured | 1421 | Only Solar Pro 4 measured |
| LMArena Text: mathematical work | Not measured | 1427 | Only Solar Pro 4 measured |
| Neither model has a result on the other 9 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | GPT-5.1-Codex | Solar Pro 4 | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 86.0% | Not measured | Only GPT-5.1-Codex measured |
| LMArena Text: science | Not measured | 1404 | Only Solar Pro 4 measured |
| LMArena Text: medicine and healthcare | Not measured | 1374 | Only Solar Pro 4 measured |
| LMArena Text: legal and government | Not measured | 1383 | Only Solar Pro 4 measured |
| LMArena Text: business and finance | Not measured | 1381 | Only Solar Pro 4 measured |
| Neither model has a result on the other 12 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index23
| Benchmark | GPT-5.1-Codex | Solar Pro 4 | Leader |
|---|---|---|---|
| Design Arena: websites | 1162 | 1176 | Solar Pro 4 |
| Design Arena: UI components | 1237 | 1150 | GPT-5.1-Codex |
| Design Arena: game dev | 1138 | 1170 | Solar Pro 4 |
| Design Arena: data viz | 1213 | 1177 | GPT-5.1-Codex |
| Design Arena: 3D | Not measured | 1178 | Only Solar Pro 4 measured |
| Design Arena: all code categories | 1153 | 1182 | Solar Pro 4 |
| Neither model has a result on the other 3 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-5.1-Codex | Solar Pro 4 | Leader |
|---|---|---|---|
| IFBench | 70.0% | Not measured | Only GPT-5.1-Codex measured |
| Long context reasoning (AA-LCR) | 69.3% | 70.7% | Solar Pro 4 |
| LMArena Text | Not measured | 1388 | Only Solar Pro 4 measured |
| LMArena Text: instruction following | Not measured | 1375 | Only Solar Pro 4 measured |
| LMArena Text: creative writing | Not measured | 1317 | Only Solar Pro 4 measured |
| LMArena Text: English | Not measured | 1414 | Only Solar Pro 4 measured |
| LMArena Text: non-English | Not measured | 1363 | Only Solar Pro 4 measured |
| LMArena Text: Chinese | Not measured | 1422 | Only Solar Pro 4 measured |
| LMArena Text: German | Not measured | 1358 | Only Solar Pro 4 measured |
| LMArena Text: Japanese | Not measured | 1320 | Only Solar Pro 4 measured |
| LMArena Text: Korean | Not measured | 1383 | Only Solar Pro 4 measured |
| LMArena Text: French | Not measured | 1400 | Only Solar Pro 4 measured |
| LMArena Text: Spanish | Not measured | 1409 | Only Solar Pro 4 measured |
| LMArena Text: Russian | Not measured | 1357 | Only Solar Pro 4 measured |
| LMArena Text: Polish | Not measured | 1304 | Only Solar Pro 4 measured |
| LMArena Text: multi-turn | Not measured | 1385 | Only Solar Pro 4 measured |
| LMArena Text: longer queries | Not measured | 1382 | Only Solar Pro 4 measured |
| LMArena Text: writing and language | Not measured | 1344 | Only Solar Pro 4 measured |
| LMArena Text: entertainment and media | Not measured | 1332 | Only Solar Pro 4 measured |
| Neither model has a result on the other 27 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.1-Codex | 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 | OpenAI GPT-5.1-Codex | Upstage Solar Pro 4 |
|---|---|---|
| Maker | OpenAI | Upstage |
| Weights | No public weights listed | No public weights listed |
| Released | November 13, 2025 | August 10, 2026 |
| Context window | 400K | 524K |
| Input $/Mtok | $1.25 | $0.15 |
| Output $/Mtok | $10.00 | $0.60 |
| Coding index | 50.5 | 24.4 |
| Independent measurements behind it | 2 | 1 |
| Cost per solved task | $0.892 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.1-Codex better than Solar Pro 4 for coding?
Pick GPT-5.1-Codex for coding: it scores 50.5 on the Vibe Coding Index against 24.4 for Solar Pro 4. Pick Solar Pro 4 when output tokens cost 16.7x less, or when the context window is larger, 524K against 400K tokens.
Which is cheaper, GPT-5.1-Codex or Solar Pro 4?
GPT-5.1-Codex costs $1.25 per million input tokens and $10.00 per million output tokens; Solar Pro 4 costs $0.15 and $0.60. Cost per solved task is known for GPT-5.1-Codex only.
Which has the bigger context window, GPT-5.1-Codex or Solar Pro 4?
Solar Pro 4, with 524K tokens against 400K.
How many benchmarks is the GPT-5.1-Codex vs Solar Pro 4 comparison based on?
13 benchmarks have a result for both models as of October 21, 2026. GPT-5.1-Codex'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.