GPT-5.2-Codex vs Solar Mini 4
GPT-5.2-Codex leads Solar Mini 4 on the Artificial Analysis Intelligence Index, 28.5 to 24.1, and Solar Mini 4 costs 70.0x less per output token ($0.20 vs $14.00 per million). Updated October 21, 2026; 3 benchmarks have a result for both.
GPT-5.2-Codex or Solar Mini 4: which to pick
Only GPT-5.2-Codex has a coding score, 45.4 on the Vibe Coding Index; Solar Mini 4 has none, so the two cannot be ranked on coding.
Pick Solar Mini 4 for output tokens 70.0x cheaper ($0.20 vs $14.00 per million) and a larger context window (524K against 400K tokens).
- Shared results
- 3
- GPT-5.2-Codex only
- 19
- Solar Mini 4 only
- 4
- Like-for-like categories
- 3 of 9
Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.
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, six public coding benchmarks
No call
Only GPT-5.2-Codex has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
GPT-5.2-Codex
GPT-5.2-Codex leads, 28.5 against 24.1.
Same board, both measured
Web design
Design Arena: websites
No call
Only Solar Mini 4 has a Design Arena: websites result, 1159.
Directional only
Long documents
Listed context window
Solar Mini 4
Solar Mini 4 takes 524K tokens against 400K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Solar Mini 4
GPT-5.2-Codex $0.0088, Solar Mini 4 $0.0001 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-5.2-Codex has the number, $0.43.
Directional only
At a glance
- Coding index
- GPT-5.2-Codex 45.4 from 3 benchmarks, Solar Mini 4 not benchmarked.
- Widest category
- Reasoning, 9.9 points apart on average over 1 shared benchmark.
- Widest single gap
- Humanity's Last Exam (Artificial Analysis run): GPT-5.2-Codex 35.7% against Solar Mini 4 25.8%, 9.9 points apart on a 0 to 100 scale.
- Output price
- GPT-5.2-Codex $14.00 against Solar Mini 4 $0.20 per million output tokens, 70.0x apart.
- Context window
- GPT-5.2-Codex takes 400K tokens, Solar Mini 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-5.2-Codex | Bars | Solar Mini 4 | Ties |
|---|---|---|---|---|
| Intelligence | 1 | 0 | ||
| Reasoning | 1 | 0 | ||
| General | 0 | 1 | ||
| All shared boards | 2 | 1 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index12 boards, none shared
| Benchmark | GPT-5.2-Codex | Solar Mini 4 | Leader |
|---|---|---|---|
| SWE-bench Verified | 72.8% | Not measured | Only GPT-5.2-Codex measured |
| SWE-bench Multilingual | 66.3% | Not measured | Only GPT-5.2-Codex measured |
| LMArena WebDev | 1339 | Not measured | Only GPT-5.2-Codex measured |
| LiveCodeBench (Vals AI) | 88.0% | Not measured | Only GPT-5.2-Codex measured |
| SWE-bench Verified (Vals AI) | 72.4% | Not measured | Only GPT-5.2-Codex measured |
| Vibe Code Bench (Vals AI) | 37.9% | Not measured | Only GPT-5.2-Codex measured |
| SciCode | Not measured | 47.6% | Only Solar Mini 4 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 37.1% | Not measured | Only GPT-5.2-Codex measured |
| Terminal-Bench | 66.5% | Not measured | Only GPT-5.2-Codex measured |
| ALE-Bench | 1299.9 | Not measured | Only GPT-5.2-Codex measured |
| LMArena WebDev: React | 1329 | Not measured | Only GPT-5.2-Codex measured |
| LMArena WebDev: HTML | 1348 | Not measured | Only GPT-5.2-Codex measured |
| Neither model has a result on the other 27 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5.2-Codex | Solar Mini 4 | Leader |
|---|---|---|---|
| AA Intelligence Index | 28.5 | 24.1 | GPT-5.2-Codex |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | GPT-5.2-Codex | Solar Mini 4 | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | 1051 | Not measured | Only GPT-5.2-Codex measured |
| Design Arena: agents building full-stack apps | 993 | Not measured | Only GPT-5.2-Codex measured |
| Design Arena: agents building mobile apps | 1090 | Not measured | Only GPT-5.2-Codex measured |
| Design Arena: agents building Android apps | 1176 | Not measured | Only GPT-5.2-Codex measured |
| Design Arena: agents building Godot games | 1142 | Not measured | Only GPT-5.2-Codex measured |
| τ²-Bench Telecom | 92.1% | Not measured | Only GPT-5.2-Codex measured |
| Neither model has a result on the other 35 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5.2-Codex | Solar Mini 4 | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 89.9% | Not measured | Only GPT-5.2-Codex measured |
| Humanity's Last Exam (Artificial Analysis run) | 35.7% | 25.8% | GPT-5.2-Codex |
| Neither model has a result on the other 20 boards here | |||
MathNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.2-Codex | Solar Mini 4 | Leader |
|---|---|---|---|
| Neither model has a result on 13 boards here | |||
KnowledgeNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.2-Codex | Solar Mini 4 | Leader |
|---|---|---|---|
| Neither model has a result on 18 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | GPT-5.2-Codex | Solar Mini 4 | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1159 | Only Solar Mini 4 measured |
| Design Arena: game dev | Not measured | 1109 | Only Solar Mini 4 measured |
| Design Arena: all code categories | Not measured | 1150 | Only Solar Mini 4 measured |
| Neither model has a result on the other 6 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-5.2-Codex | Solar Mini 4 | Leader |
|---|---|---|---|
| IFBench | 77.6% | Not measured | Only GPT-5.2-Codex measured |
| Long context reasoning (AA-LCR) | 82.3% | 83.3% | Solar Mini 4 |
| Neither model has a result on the other 44 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.2-Codex | Solar Mini 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 Mini 4 costs less
Repository review
50K input + 3K output tokens
Solar Mini 4 costs less
Agent loop
200K input + 10K output tokens
Solar Mini 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-5.2-Codex | Upstage Solar Mini 4 |
|---|---|---|
| Maker | OpenAI | Upstage |
| Weights | No public weights listed | No public weights listed |
| Released | January 14, 2026 | September 23, 2026 |
| Context window | 400K | 524K |
| Input $/Mtok | $1.75 | $0.05 |
| Output $/Mtok | $14.00 | $0.20 |
| Coding index | 45.4 | Not benchmarked |
| Independent measurements behind it | 3 | 0 |
| Cost per solved task | $0.43 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.2-Codex better than Solar Mini 4 for coding?
Only GPT-5.2-Codex has a coding score, 45.4 on the Vibe Coding Index; Solar Mini 4 has none, so the two cannot be ranked on coding. Pick Solar Mini 4 for output tokens 70.0x cheaper ($0.20 vs $14.00 per million) and a larger context window (524K against 400K tokens).
Which is cheaper, GPT-5.2-Codex or Solar Mini 4?
GPT-5.2-Codex costs $1.75 per million input tokens and $14.00 per million output tokens; Solar Mini 4 costs $0.05 and $0.20. Cost per solved task is known for GPT-5.2-Codex only.
Which has the bigger context window, GPT-5.2-Codex or Solar Mini 4?
Solar Mini 4, with 524K tokens against 400K.
How many benchmarks is the GPT-5.2-Codex vs Solar Mini 4 comparison based on?
3 benchmarks have a result for both models as of October 21, 2026. GPT-5.2-Codex's coding index rests on 3 independent benchmarks and Solar Mini 4's on 0. Where only one model has a result, the page says so instead of naming a winner.