GPT-3.5 Turbo vs Solar Mini 4
Solar Mini 4 leads GPT-3.5 Turbo on the Artificial Analysis Intelligence Index, 24.1 to 5.5, and Solar Mini 4 costs 7.5x less per output token ($0.20 vs $1.50 per million). Updated October 22, 2026; 1 benchmarks have a result for both.
GPT-3.5 Turbo or Solar Mini 4: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick GPT-3.5 Turbo for work measured by AA Intelligence Index, where it leads.
- Shared results
- 1
- GPT-3.5 Turbo only
- 12
- Solar Mini 4 only
- 7
- Like-for-like categories
- 1 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
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
Solar Mini 4
Solar Mini 4 leads, 24.1 against 5.5.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only GPT-3.5 Turbo has a GPQA Diamond result, 30.6%.
Directional only
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 16K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Solar Mini 4
GPT-3.5 Turbo $0.0013, Solar Mini 4 $0.0001 per turn.
List prices
At a glance
- Coding index
- GPT-3.5 Turbo not benchmarked, Solar Mini 4 not benchmarked.
- Widest category
- Intelligence, 18.6 points apart on average over 1 shared benchmark.
- Widest single gap
- AA Intelligence Index: GPT-3.5 Turbo 5.5 against Solar Mini 4 24.1, 18.6 points apart on a 0 to 100 scale.
- Output price
- GPT-3.5 Turbo $1.50 against Solar Mini 4 $0.20 per million output tokens, 7.5x apart.
- Context window
- GPT-3.5 Turbo takes 16K 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-3.5 Turbo | Bars | Solar Mini 4 | Ties |
|---|---|---|---|---|
| Intelligence | 0 | 1 | ||
| All shared boards | 0 | 1 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index3 boards, none shared
| Benchmark | GPT-3.5 Turbo | Solar Mini 4 | Leader |
|---|---|---|---|
| AA Coding Index | 10.7 | Not measured | Only GPT-3.5 Turbo measured |
| SciCode | Not measured | 47.6% | Only Solar Mini 4 measured |
| SciCode | 0.0% | Not measured | Only GPT-3.5 Turbo measured |
| Neither model has a result on the other 40 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-3.5 Turbo | Solar Mini 4 | Leader |
|---|---|---|---|
| AA Intelligence Index | 5.5 | 24.1 | Solar Mini 4 |
| Neither model has a result on the other 1 board here | |||
Agentic workNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-3.5 Turbo | Solar Mini 4 | Leader |
|---|---|---|---|
| Neither model has a result on 42 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | GPT-3.5 Turbo | Solar Mini 4 | Leader |
|---|---|---|---|
| GPQA Diamond | 30.6% | Not measured | Only GPT-3.5 Turbo measured |
| GPQA Diamond (Artificial Analysis run) | 29.7% | Not measured | Only GPT-3.5 Turbo measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 25.8% | Only Solar Mini 4 measured |
| BIG-Bench Hard | 61.6% | Not measured | Only GPT-3.5 Turbo measured |
| Neither model has a result on the other 19 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | GPT-3.5 Turbo | Solar Mini 4 | Leader |
|---|---|---|---|
| GSM8K | 57.8% | Not measured | Only GPT-3.5 Turbo measured |
| Neither model has a result on the other 13 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | GPT-3.5 Turbo | Solar Mini 4 | Leader |
|---|---|---|---|
| LegalBench (Vals AI) | 64.4% | Not measured | Only GPT-3.5 Turbo measured |
| MedQA (Vals AI) | 58.5% | Not measured | Only GPT-3.5 Turbo measured |
| MMLU Pro (Artificial Analysis run) | 46.2% | Not measured | Only GPT-3.5 Turbo measured |
| MMLU | 68.5% | Not measured | Only GPT-3.5 Turbo measured |
| Neither model has a result on the other 16 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | GPT-3.5 Turbo | Solar Mini 4 | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1159 | Only Solar Mini 4 measured |
| Design Arena: UI components | Not measured | 1073 | Only Solar Mini 4 measured |
| Design Arena: game dev | Not measured | 1105 | Only Solar Mini 4 measured |
| Design Arena: all code categories | Not measured | 1149 | Only Solar Mini 4 measured |
| Neither model has a result on the other 5 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | GPT-3.5 Turbo | Solar Mini 4 | Leader |
|---|---|---|---|
| Long context reasoning (AA-LCR) | Not measured | 83.3% | Only Solar Mini 4 measured |
| DTBench | 48.5% | Not measured | Only GPT-3.5 Turbo measured |
| LMCA | 9.7% | Not measured | Only GPT-3.5 Turbo measured |
| Neither model has a result on the other 45 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-3.5 Turbo | 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-3.5 Turbo | Upstage Solar Mini 4 |
|---|---|---|
| Maker | OpenAI | Upstage |
| Weights | No public weights listed | No public weights listed |
| Released | May 28, 2023 | September 23, 2026 |
| Context window | 16K | 524K |
| Input $/Mtok | $0.50 | $0.05 |
| Output $/Mtok | $1.50 | $0.20 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-3.5 Turbo better than Solar Mini 4 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-3.5 Turbo for work measured by AA Intelligence Index, where it leads.
Which is cheaper, GPT-3.5 Turbo or Solar Mini 4?
GPT-3.5 Turbo costs $0.50 per million input tokens and $1.50 per million output tokens; Solar Mini 4 costs $0.05 and $0.20. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-3.5 Turbo or Solar Mini 4?
Solar Mini 4, with 524K tokens against 16K.
How many benchmarks is the GPT-3.5 Turbo vs Solar Mini 4 comparison based on?
1 benchmarks have a result for both models as of October 22, 2026. GPT-3.5 Turbo's coding index rests on 0 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.