GPT-3.5 Turbo vs GPT-5.5 Pro
GPT-3.5 Turbo costs 120.0x less per output token than GPT-5.5 Pro ($1.50 vs $180.00 per million). Updated October 22, 2026; 2 benchmarks have a result for both.
GPT-3.5 Turbo or GPT-5.5 Pro: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick GPT-3.5 Turbo for output tokens 120.0x cheaper ($1.50 vs $180.00 per million) and work measured by DTBench or LMCA, where it leads.
- Shared results
- 2
- GPT-3.5 Turbo only
- 11
- GPT-5.5 Pro 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
No call
Only GPT-3.5 Turbo has a AA Intelligence Index result, 5.5.
Directional only
Reasoning
GPQA Diamond
No call
Only GPT-3.5 Turbo has a GPQA Diamond result, 30.6%.
Directional only
Long documents
Listed context window
GPT-5.5 Pro
GPT-5.5 Pro takes 1.05M tokens against 16K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-3.5 Turbo
GPT-3.5 Turbo $0.0013, GPT-5.5 Pro $0.120 per turn.
List prices
At a glance
- Coding index
- GPT-3.5 Turbo not benchmarked, GPT-5.5 Pro not benchmarked.
- Widest category
- General, 45.9 points apart on average over 2 shared benchmarks.
- Widest single gap
- DTBench: GPT-3.5 Turbo 48.5% against GPT-5.5 Pro 96.0%, 47.5 points apart on a 0 to 100 scale.
- Output price
- GPT-3.5 Turbo $1.50 against GPT-5.5 Pro $180.00 per million output tokens, 120.0x apart.
- Context window
- GPT-3.5 Turbo takes 16K tokens, GPT-5.5 Pro 1.05M.
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 | GPT-5.5 Pro | Ties |
|---|---|---|---|---|
| General | 0 | 2 | ||
| All shared boards | 0 | 2 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index2 boards, none shared
| Benchmark | GPT-3.5 Turbo | GPT-5.5 Pro | Leader |
|---|---|---|---|
| AA Coding Index | 10.7 | Not measured | Only GPT-3.5 Turbo measured |
| SciCode | 0.0% | Not measured | Only GPT-3.5 Turbo measured |
| Neither model has a result on the other 41 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GPT-3.5 Turbo | GPT-5.5 Pro | Leader |
|---|---|---|---|
| AA Intelligence Index | 5.5 | Not measured | Only GPT-3.5 Turbo measured |
| Epoch Capabilities Index | Not measured | 162.9 | Only GPT-5.5 Pro measured |
Agentic workNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-3.5 Turbo | GPT-5.5 Pro | Leader |
|---|---|---|---|
| Neither model has a result on 42 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | GPT-3.5 Turbo | GPT-5.5 Pro | 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 |
| ARC-AGI | Not measured | 96.5% | Only GPT-5.5 Pro measured |
| ARC-AGI-2 | Not measured | 84.6% | Only GPT-5.5 Pro measured |
| SimpleBench | Not measured | 76.9% | Only GPT-5.5 Pro measured |
| Chess puzzles | Not measured | 62.0% | Only GPT-5.5 Pro measured |
| BIG-Bench Hard | 61.6% | Not measured | Only GPT-3.5 Turbo measured |
| Neither model has a result on the other 16 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | GPT-3.5 Turbo | GPT-5.5 Pro | Leader |
|---|---|---|---|
| FrontierMath, tiers 1 to 3 | Not measured | 87.7% | Only GPT-5.5 Pro measured |
| FrontierMath, tier 4 | Not measured | 78.0% | Only GPT-5.5 Pro measured |
| GSM8K | 57.8% | Not measured | Only GPT-3.5 Turbo measured |
| Neither model has a result on the other 11 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | GPT-3.5 Turbo | GPT-5.5 Pro | 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 designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-3.5 Turbo | GPT-5.5 Pro | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index02
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-3.5 Turbo | GPT-5.5 Pro | 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
GPT-3.5 Turbo costs less
Repository review
50K input + 3K output tokens
GPT-3.5 Turbo costs less
Agent loop
200K input + 10K output tokens
GPT-3.5 Turbo 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 | OpenAI GPT-5.5 Pro |
|---|---|---|
| Maker | OpenAI | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | May 28, 2023 | April 24, 2026 |
| Context window | 16K | 1.05M |
| Input $/Mtok | $0.50 | $30.00 |
| Output $/Mtok | $1.50 | $180.00 |
| 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 GPT-5.5 Pro for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-3.5 Turbo for output tokens 120.0x cheaper ($1.50 vs $180.00 per million) and work measured by DTBench or LMCA, where it leads.
Which is cheaper, GPT-3.5 Turbo or GPT-5.5 Pro?
GPT-3.5 Turbo costs $0.50 per million input tokens and $1.50 per million output tokens; GPT-5.5 Pro costs $30.00 and $180.00. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-3.5 Turbo or GPT-5.5 Pro?
GPT-5.5 Pro, with 1.05M tokens against 16K.
How many benchmarks is the GPT-3.5 Turbo vs GPT-5.5 Pro comparison based on?
2 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 GPT-5.5 Pro's on 0. Where only one model has a result, the page says so instead of naming a winner.