GPT-3.5 Turbo vs Hy3 preview
Hy3 preview leads GPT-3.5 Turbo on the Artificial Analysis Intelligence Index, 25.3 to 5.5, and Hy3 preview costs 2.5x less per output token ($0.60 vs $1.50 per million). Updated October 22, 2026; 3 benchmarks have a result for both.
GPT-3.5 Turbo or Hy3 preview: 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 Coding Index or AA Intelligence Index, where it leads.
- Shared results
- 3
- GPT-3.5 Turbo only
- 10
- Hy3 preview only
- 33
- 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
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
Hy3 preview
Hy3 preview leads, 25.3 against 5.5.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Hy3 preview has a AA Agentic Index result, 24.1.
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
Hy3 preview
Hy3 preview takes 262K tokens against 16K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Hy3 preview
GPT-3.5 Turbo $0.0013, Hy3 preview $0.0005 per turn.
List prices
At a glance
- Coding index
- GPT-3.5 Turbo not benchmarked, Hy3 preview not benchmarked.
- Widest category
- Reasoning, 57.0 points apart on average over 1 shared benchmark.
- Widest single gap
- GPQA Diamond (Artificial Analysis run): GPT-3.5 Turbo 29.7% against Hy3 preview 86.7%, 57.0 points apart on a 0 to 100 scale.
- Output price
- GPT-3.5 Turbo $1.50 against Hy3 preview $0.60 per million output tokens, 2.5x apart.
- Context window
- GPT-3.5 Turbo takes 16K tokens, Hy3 preview 262K.
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 | Hy3 preview | Ties |
|---|---|---|---|---|
| Coding | 0 | 1 | ||
| Intelligence | 0 | 1 | ||
| Reasoning | 0 | 1 | ||
| All shared boards | 0 | 3 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
| Benchmark | GPT-3.5 Turbo | Hy3 preview | Leader |
|---|---|---|---|
| LMArena WebDev | Not measured | 1357 | Only Hy3 preview measured |
| AA Coding Index | 10.7 | 58.8 | Hy3 preview |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 34.1% | Only Hy3 preview measured |
| LMArena Text: coding | Not measured | 1421 | Only Hy3 preview measured |
| LMArena Text: software and IT | Not measured | 1423 | Only Hy3 preview measured |
| LMArena WebDev: React | Not measured | 1349 | Only Hy3 preview measured |
| LMArena WebDev: HTML | Not measured | 1356 | Only Hy3 preview measured |
| SciCode | 0.0% | Not measured | Only GPT-3.5 Turbo measured |
| Neither model has a result on the other 31 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-3.5 Turbo | Hy3 preview | Leader |
|---|---|---|---|
| AA Intelligence Index | 5.5 | 25.3 | Hy3 preview |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GPT-3.5 Turbo | Hy3 preview | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 24.1 | Only Hy3 preview measured |
| τ²-Bench Telecom | Not measured | 92.7% | Only Hy3 preview measured |
| Neither model has a result on the other 39 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-3.5 Turbo | Hy3 preview | Leader |
|---|---|---|---|
| GPQA Diamond | 30.6% | Not measured | Only GPT-3.5 Turbo measured |
| GPQA Diamond (Artificial Analysis run) | 29.7% | 86.7% | Hy3 preview |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 27.8% | Only Hy3 preview measured |
| BIG-Bench Hard | 61.6% | Not measured | Only GPT-3.5 Turbo measured |
| LMArena Text: hard prompts | Not measured | 1413 | Only Hy3 preview measured |
| LMArena Text: expert | Not measured | 1422 | Only Hy3 preview measured |
| LMArena Text: hard prompts in English | Not measured | 1416 | Only Hy3 preview measured |
| Neither model has a result on the other 15 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | GPT-3.5 Turbo | Hy3 preview | Leader |
|---|---|---|---|
| GSM8K | 57.8% | Not measured | Only GPT-3.5 Turbo measured |
| LMArena Text: math | Not measured | 1424 | Only Hy3 preview measured |
| LMArena Text: mathematical work | Not measured | 1442 | Only Hy3 preview measured |
| Neither model has a result on the other 10 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | GPT-3.5 Turbo | Hy3 preview | 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 |
| LMArena Text: science | Not measured | 1416 | Only Hy3 preview measured |
| LMArena Text: medicine and healthcare | Not measured | 1405 | Only Hy3 preview measured |
| LMArena Text: legal and government | Not measured | 1430 | Only Hy3 preview measured |
| LMArena Text: business and finance | Not measured | 1397 | Only Hy3 preview measured |
| Neither model has a result on the other 10 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-3.5 Turbo | Hy3 preview | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index17 boards, none shared
| Benchmark | GPT-3.5 Turbo | Hy3 preview | Leader |
|---|---|---|---|
| IFBench | Not measured | 63.1% | Only Hy3 preview measured |
| Long context reasoning (AA-LCR) | Not measured | 64.7% | Only Hy3 preview measured |
| DTBench | 48.5% | Not measured | Only GPT-3.5 Turbo measured |
| LMCA | 9.7% | Not measured | Only GPT-3.5 Turbo measured |
| LMArena Text | Not measured | 1401 | Only Hy3 preview measured |
| LMArena Text: instruction following | Not measured | 1383 | Only Hy3 preview measured |
| LMArena Text: creative writing | Not measured | 1339 | Only Hy3 preview measured |
| LMArena Text: English | Not measured | 1409 | Only Hy3 preview measured |
| LMArena Text: non-English | Not measured | 1390 | Only Hy3 preview measured |
| LMArena Text: Chinese | Not measured | 1435 | Only Hy3 preview measured |
| LMArena Text: French | Not measured | 1425 | Only Hy3 preview measured |
| LMArena Text: Spanish | Not measured | 1399 | Only Hy3 preview measured |
| LMArena Text: Russian | Not measured | 1399 | Only Hy3 preview measured |
| LMArena Text: multi-turn | Not measured | 1411 | Only Hy3 preview measured |
| LMArena Text: longer queries | Not measured | 1402 | Only Hy3 preview measured |
| LMArena Text: writing and language | Not measured | 1370 | Only Hy3 preview measured |
| LMArena Text: entertainment and media | Not measured | 1352 | Only Hy3 preview measured |
| Neither model has a result on the other 29 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-3.5 Turbo | Hy3 preview | 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
Hy3 preview costs less
Repository review
50K input + 3K output tokens
Hy3 preview costs less
Agent loop
200K input + 10K output tokens
Hy3 preview 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 | Tencent Hy3 preview |
|---|---|---|
| Maker | OpenAI | Tencent |
| Weights | No public weights listed | Open weights |
| Released | May 28, 2023 | April 22, 2026 |
| Context window | 16K | 262K |
| Input $/Mtok | $0.50 | $0.18 |
| Output $/Mtok | $1.50 | $0.60 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-3.5 Turbo better than Hy3 preview 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 Coding Index or AA Intelligence Index, where it leads.
Which is cheaper, GPT-3.5 Turbo or Hy3 preview?
GPT-3.5 Turbo costs $0.50 per million input tokens and $1.50 per million output tokens; Hy3 preview costs $0.18 and $0.60. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-3.5 Turbo or Hy3 preview?
Hy3 preview, with 262K tokens against 16K.
How many benchmarks is the GPT-3.5 Turbo vs Hy3 preview comparison based on?
3 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 Hy3 preview's on 1. Where only one model has a result, the page says so instead of naming a winner.