GPT-3.5 Turbo (older v0613) vs GPT-4o
GPT-3.5 Turbo (older v0613) costs 5.0x less per output token than GPT-4o ($2.00 vs $10.00 per million). Updated October 22, 2026; 1 benchmarks have a result for both.
GPT-3.5 Turbo (older v0613) or GPT-4o: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick GPT-3.5 Turbo (older v0613) for output tokens 5.0x cheaper ($2.00 vs $10.00 per million) and work measured by MMLU, where it leads.
- Shared results
- 1
- GPT-3.5 Turbo (older v0613) only
- 2
- GPT-4o only
- 27
- 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
Web design
Design Arena: websites
No call
Only GPT-4o has a Design Arena: websites result, 831.
Directional only
Long documents
Listed context window
GPT-4o
GPT-4o takes 128K tokens against 4K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-3.5 Turbo (older v0613)
GPT-3.5 Turbo (older v0613) $0.0020, GPT-4o $0.0075 per turn.
List prices
At a glance
- Coding index
- GPT-3.5 Turbo (older v0613) not benchmarked, GPT-4o not benchmarked.
- Widest category
- Knowledge, 19.2 points apart on average over 1 shared benchmark.
- Widest single gap
- MMLU: GPT-3.5 Turbo (older v0613) 68.9% against GPT-4o 88.1%, 19.2 points apart on a 0 to 100 scale.
- Output price
- GPT-3.5 Turbo (older v0613) $2.00 against GPT-4o $10.00 per million output tokens, 5.0x apart.
- Context window
- GPT-3.5 Turbo (older v0613) takes 4K tokens, GPT-4o 128K.
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 (older v0613) | Bars | GPT-4o | Ties |
|---|---|---|---|---|
| Knowledge | 0 | 1 | ||
| All shared boards | 0 | 1 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index7 boards, none shared
| Benchmark | GPT-3.5 Turbo (older v0613) | GPT-4o | Leader |
|---|---|---|---|
| SWE-bench Verified | Not measured | 38.8% | Only GPT-4o measured |
| SWE-bench Lite | Not measured | 38.0% | Only GPT-4o measured |
| SWE-bench (full test set) | Not measured | 18.8% | Only GPT-4o measured |
| SWE-bench Multimodal | Not measured | 30.4% | Only GPT-4o measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 30.9% | Only GPT-4o measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 8.3% | Only GPT-4o measured |
| SciCode | Not measured | 1.5% | Only GPT-4o measured |
| Neither model has a result on the other 36 boards here | |||
IntelligenceNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-3.5 Turbo (older v0613) | GPT-4o | Leader |
|---|---|---|---|
| Neither model has a result on 2 boards here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GPT-3.5 Turbo (older v0613) | GPT-4o | Leader |
|---|---|---|---|
| τ²-Bench Telecom | Not measured | 25.1% | Only GPT-4o measured |
| GDPval | Not measured | 9.9% | Only GPT-4o measured |
| Neither model has a result on the other 40 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | GPT-3.5 Turbo (older v0613) | GPT-4o | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 54.3% | Only GPT-4o measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 2.4% | Only GPT-4o measured |
| ARC-AGI | Not measured | 4.5% | Only GPT-4o measured |
| ARC-AGI-2 | Not measured | 0.0% | Only GPT-4o measured |
| Neither model has a result on the other 19 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | GPT-3.5 Turbo (older v0613) | GPT-4o | Leader |
|---|---|---|---|
| AA Math Index | Not measured | 6.0 | Only GPT-4o measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 6.0% | Only GPT-4o measured |
| GSM8K | 46.9% | Not measured | Only GPT-3.5 Turbo (older v0613) measured |
| MathArena | Not measured | 3.6% | Only GPT-4o measured |
| Neither model has a result on the other 10 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-3.5 Turbo (older v0613) | GPT-4o | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | Not measured | 74.8% | Only GPT-4o measured |
| MMLU | 68.9% | 88.1% | GPT-4o |
| Neither model has a result on the other 18 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | GPT-3.5 Turbo (older v0613) | GPT-4o | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 831 | Only GPT-4o measured |
| Design Arena: UI components | Not measured | 883 | Only GPT-4o measured |
| Design Arena: game dev | Not measured | 906 | Only GPT-4o measured |
| Design Arena: data viz | Not measured | 858 | Only GPT-4o measured |
| Design Arena: 3D | Not measured | 868 | Only GPT-4o measured |
| Design Arena: all code categories | Not measured | 860 | Only GPT-4o measured |
| Neither model has a result on the other 3 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | GPT-3.5 Turbo (older v0613) | GPT-4o | Leader |
|---|---|---|---|
| IFBench | Not measured | 34.3% | Only GPT-4o measured |
| Long context reasoning (AA-LCR) | Not measured | 49.3% | Only GPT-4o measured |
| DTBench | Not measured | 64.5% | Only GPT-4o measured |
| LMCA | Not measured | 16.6% | Only GPT-4o measured |
| WinoGrande | 81.6% | Not measured | Only GPT-3.5 Turbo (older v0613) measured |
| Neither model has a result on the other 43 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-3.5 Turbo (older v0613) | GPT-4o | 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 (older v0613) costs less
Repository review
50K input + 3K output tokens
GPT-3.5 Turbo (older v0613) costs less
Agent loop
200K input + 10K output tokens
GPT-3.5 Turbo (older v0613) 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 (older v0613) | OpenAI GPT-4o |
|---|---|---|
| Maker | OpenAI | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | January 25, 2024 | May 13, 2024 |
| Context window | 4K | 128K |
| Input $/Mtok | $1.00 | $2.50 |
| Output $/Mtok | $2.00 | $10.00 |
| 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 (older v0613) better than GPT-4o for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-3.5 Turbo (older v0613) for output tokens 5.0x cheaper ($2.00 vs $10.00 per million) and work measured by MMLU, where it leads.
Which is cheaper, GPT-3.5 Turbo (older v0613) or GPT-4o?
GPT-3.5 Turbo (older v0613) costs $1.00 per million input tokens and $2.00 per million output tokens; GPT-4o costs $2.50 and $10.00. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-3.5 Turbo (older v0613) or GPT-4o?
GPT-4o, with 128K tokens against 4K.
How many benchmarks is the GPT-3.5 Turbo (older v0613) vs GPT-4o comparison based on?
1 benchmarks have a result for both models as of October 22, 2026. GPT-3.5 Turbo (older v0613)'s coding index rests on 0 independent benchmarks and GPT-4o's on 0. Where only one model has a result, the page says so instead of naming a winner.