GPT-3.5 Turbo vs Grok 4.7
Grok 4.7 leads GPT-3.5 Turbo on the Artificial Analysis Intelligence Index, 46.4 to 5.5, and GPT-3.5 Turbo costs 4.0x less per output token ($1.50 vs $6.00 per million). Updated October 22, 2026; 4 benchmarks have a result for both.
GPT-3.5 Turbo or Grok 4.7: which to pick
Only Grok 4.7 has a coding score, 66.7 on the Vibe Coding Index; GPT-3.5 Turbo has none, so the two cannot be ranked on coding.
Pick GPT-3.5 Turbo for output tokens 4.0x cheaper ($1.50 vs $6.00 per million).
- Shared results
- 4
- GPT-3.5 Turbo only
- 9
- Grok 4.7 only
- 95
- 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 Grok 4.7 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Grok 4.7
Grok 4.7 leads, 46.4 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 Grok 4.7 has a Design Arena: websites result, 1255.
Directional only
General
Vals Index
No call
Only Grok 4.7 has a Vals Index result, 58.6%.
Directional only
Long documents
Listed context window
Grok 4.7
Grok 4.7 takes 500K tokens against 16K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-3.5 Turbo
GPT-3.5 Turbo $0.0013, Grok 4.7 $0.0050 per turn.
List prices
At a glance
- Coding index
- GPT-3.5 Turbo not benchmarked, Grok 4.7 66.7 from 5 benchmarks.
- Widest category
- General, 43.6 points apart on average over 2 shared benchmarks.
- Widest single gap
- DTBench: GPT-3.5 Turbo 48.5% against Grok 4.7 96.0%, 47.5 points apart on a 0 to 100 scale.
- Output price
- GPT-3.5 Turbo $1.50 against Grok 4.7 $6.00 per million output tokens, 4.0x apart.
- Context window
- GPT-3.5 Turbo takes 16K tokens, Grok 4.7 500K.
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 | Grok 4.7 | Ties |
|---|---|---|---|---|
| Intelligence | 0 | 1 | ||
| Knowledge | 0 | 1 | ||
| General | 0 | 2 | ||
| All shared boards | 0 | 4 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index20 boards, none shared
| Benchmark | GPT-3.5 Turbo | Grok 4.7 | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 84.5% | Only Grok 4.7 measured |
| LMArena WebDev | Not measured | 1637 | Only Grok 4.7 measured |
| AA Coding Index | 10.7 | Not measured | Only GPT-3.5 Turbo measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 28.8% | Only Grok 4.7 measured |
| Vibe Code Bench (Vals AI) | Not measured | 86.2% | Only Grok 4.7 measured |
| Code migration (Vals AI) | Not measured | 44.8% | Only Grok 4.7 measured |
| ProgramBench (Vals AI) | Not measured | 0.5% | Only Grok 4.7 measured |
| IOI (Vals AI) | Not measured | 57.7% | Only Grok 4.7 measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 73.4% | Only Grok 4.7 measured |
| SWE-bench Multimodal (Vals AI) | Not measured | 42.9% | Only Grok 4.7 measured |
| CyberBench (Vals AI) | Not measured | 69.5% | Only Grok 4.7 measured |
| SciCode | Not measured | 57.8% | Only Grok 4.7 measured |
| FrontierCode | Not measured | 47.6% | Only Grok 4.7 measured |
| FrontierSWE | Not measured | 29.5% | Only Grok 4.7 measured |
| LMArena Text: coding | Not measured | 1432 | Only Grok 4.7 measured |
| LMArena Text: software and IT | Not measured | 1421 | Only Grok 4.7 measured |
| LMArena WebDev: React | Not measured | 1663 | Only Grok 4.7 measured |
| LMArena WebDev: HTML | Not measured | 1627 | Only Grok 4.7 measured |
| LMArena WebDev: from an image | Not measured | 1586 | Only Grok 4.7 measured |
| SciCode | 0.0% | Not measured | Only GPT-3.5 Turbo measured |
| Neither model has a result on the other 19 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-3.5 Turbo | Grok 4.7 | Leader |
|---|---|---|---|
| AA Intelligence Index | 5.5 | 46.4 | Grok 4.7 |
| Epoch Capabilities Index | Not measured | 154.4 | Only Grok 4.7 measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index15 boards, none shared
| Benchmark | GPT-3.5 Turbo | Grok 4.7 | Leader |
|---|---|---|---|
| LiveBench research | Not measured | 86.4% | Only Grok 4.7 measured |
| LiveBench browser | Not measured | 60.0% | Only Grok 4.7 measured |
| LiveBench long agentic | Not measured | 50.1% | Only Grok 4.7 measured |
| SREBench (Vals AI) | Not measured | 3.8% | Only Grok 4.7 measured |
| Finance Agent (Vals AI) | Not measured | 52.3% | Only Grok 4.7 measured |
| Tax Agent Bench (Vals AI) | Not measured | 34.2% | Only Grok 4.7 measured |
| Legal Research Bench (Vals AI) | Not measured | 47.1% | Only Grok 4.7 measured |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 18.3% | Only Grok 4.7 measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 67.0% | Only Grok 4.7 measured |
| BioMysteryBench (Vals AI) | Not measured | 69.3% | Only Grok 4.7 measured |
| Terminal-Bench-Science (Vals AI) | Not measured | 10.0% | Only Grok 4.7 measured |
| Vals Science Index | Not measured | 34.8% | Only Grok 4.7 measured |
| Robo-bench (Vals AI) | Not measured | 0.2% | Only Grok 4.7 measured |
| APEX-Agents | Not measured | 54.6% | Only Grok 4.7 measured |
| Vending-Bench 2 | Not measured | $10,537 | Only Grok 4.7 measured |
| Neither model has a result on the other 26 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index16 boards, none shared
| Benchmark | GPT-3.5 Turbo | Grok 4.7 | Leader |
|---|---|---|---|
| GPQA Diamond | 30.6% | Not measured | Only GPT-3.5 Turbo measured |
| LiveBench reasoning | Not measured | 82.7% | Only Grok 4.7 measured |
| MysteryMechanism (Vals AI) | Not measured | 25.2% | Only Grok 4.7 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 | 43.1% | Only Grok 4.7 measured |
| GPQA Diamond (Epoch AI run) | Not measured | 92.7% | Only Grok 4.7 measured |
| ARC-AGI | Not measured | 90.2% | Only Grok 4.7 measured |
| ARC-AGI-2 | Not measured | 61.4% | Only Grok 4.7 measured |
| Chess puzzles | Not measured | 41.0% | Only Grok 4.7 measured |
| Mystery game puzzles | Not measured | 29.0% | Only Grok 4.7 measured |
| BIG-Bench Hard | 61.6% | Not measured | Only GPT-3.5 Turbo measured |
| LMArena Text: hard prompts | Not measured | 1415 | Only Grok 4.7 measured |
| LMArena Text: expert | Not measured | 1439 | Only Grok 4.7 measured |
| LMArena Text: hard prompts in English | Not measured | 1427 | Only Grok 4.7 measured |
| LMArena Vision: diagrams | Not measured | 1254 | Only Grok 4.7 measured |
| LMArena Vision: homework | Not measured | 1309 | Only Grok 4.7 measured |
| Neither model has a result on the other 6 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | GPT-3.5 Turbo | Grok 4.7 | Leader |
|---|---|---|---|
| OTIS Mock AIME | Not measured | 98.1% | Only Grok 4.7 measured |
| FrontierMath, tiers 1 to 3 | Not measured | 53.0% | Only Grok 4.7 measured |
| FrontierMath, tier 4 | Not measured | 17.1% | Only Grok 4.7 measured |
| ProofBench | Not measured | 26.0% | Only Grok 4.7 measured |
| GSM8K | 57.8% | Not measured | Only GPT-3.5 Turbo measured |
| LMArena Text: math | Not measured | 1414 | Only Grok 4.7 measured |
| LMArena Text: mathematical work | Not measured | 1435 | Only Grok 4.7 measured |
| Neither model has a result on the other 6 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-3.5 Turbo | Grok 4.7 | Leader |
|---|---|---|---|
| LegalBench (Vals AI) | 64.4% | 84.4% | Grok 4.7 |
| MedQA (Vals AI) | 58.5% | Not measured | Only GPT-3.5 Turbo measured |
| MedCode (Vals AI) | Not measured | 49.5% | Only Grok 4.7 measured |
| MMLU Pro (Artificial Analysis run) | 46.2% | Not measured | Only GPT-3.5 Turbo measured |
| SimpleQA Verified | Not measured | 56.0% | Only Grok 4.7 measured |
| MMLU | 68.5% | Not measured | Only GPT-3.5 Turbo measured |
| LMArena Text: science | Not measured | 1419 | Only Grok 4.7 measured |
| LMArena Text: medicine and healthcare | Not measured | 1395 | Only Grok 4.7 measured |
| LMArena Text: legal and government | Not measured | 1423 | Only Grok 4.7 measured |
| LMArena Text: business and finance | Not measured | 1389 | Only Grok 4.7 measured |
| Neither model has a result on the other 8 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | GPT-3.5 Turbo | Grok 4.7 | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1255 | Only Grok 4.7 measured |
| Design Arena: UI components | Not measured | 1275 | Only Grok 4.7 measured |
| Design Arena: game dev | Not measured | 1314 | Only Grok 4.7 measured |
| Design Arena: data viz | Not measured | 1238 | Only Grok 4.7 measured |
| Design Arena: 3D | Not measured | 1274 | Only Grok 4.7 measured |
| Design Arena: all code categories | Not measured | 1273 | Only Grok 4.7 measured |
| LiveBench design | Not measured | 78.0% | Only Grok 4.7 measured |
| Neither model has a result on the other 2 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | GPT-3.5 Turbo | Grok 4.7 | Leader |
|---|---|---|---|
| Vals Index | Not measured | 58.6% | Only Grok 4.7 measured |
| LiveBench data analysis | Not measured | 76.9% | Only Grok 4.7 measured |
| Public Benefits Bench (Vals AI) | Not measured | 65.6% | Only Grok 4.7 measured |
| SAGE (Vals AI) | Not measured | 40.8% | Only Grok 4.7 measured |
| MedScribe (Vals AI) | Not measured | 89.4% | Only Grok 4.7 measured |
| Long context reasoning (AA-LCR) | Not measured | 80.0% | Only Grok 4.7 measured |
| DTBench | 48.5% | 96.0% | Grok 4.7 |
| LMCA | 9.7% | 49.4% | Grok 4.7 |
| Furniture assembly | Not measured | 20.8% | Only Grok 4.7 measured |
| LMArena Text | Not measured | 1399 | Only Grok 4.7 measured |
| LMArena Text: instruction following | Not measured | 1406 | Only Grok 4.7 measured |
| LMArena Text: creative writing | Not measured | 1381 | Only Grok 4.7 measured |
| LMArena Vision | Not measured | 1231 | Only Grok 4.7 measured |
| LMArena Text: English | Not measured | 1411 | Only Grok 4.7 measured |
| LMArena Text: non-English | Not measured | 1386 | Only Grok 4.7 measured |
| LMArena Text: Chinese | Not measured | 1449 | Only Grok 4.7 measured |
| LMArena Text: German | Not measured | 1366 | Only Grok 4.7 measured |
| LMArena Text: Japanese | Not measured | 1359 | Only Grok 4.7 measured |
| LMArena Text: Korean | Not measured | 1383 | Only Grok 4.7 measured |
| LMArena Text: French | Not measured | 1431 | Only Grok 4.7 measured |
| LMArena Text: Spanish | Not measured | 1406 | Only Grok 4.7 measured |
| LMArena Text: Russian | Not measured | 1399 | Only Grok 4.7 measured |
| LMArena Text: Polish | Not measured | 1420 | Only Grok 4.7 measured |
| LMArena Text: multi-turn | Not measured | 1394 | Only Grok 4.7 measured |
| LMArena Text: longer queries | Not measured | 1416 | Only Grok 4.7 measured |
| LMArena Text: writing and language | Not measured | 1394 | Only Grok 4.7 measured |
| LMArena Text: entertainment and media | Not measured | 1376 | Only Grok 4.7 measured |
| LMArena Vision: English | Not measured | 1229 | Only Grok 4.7 measured |
| LMArena Vision: Chinese | Not measured | 1250 | Only Grok 4.7 measured |
| LMArena Vision: reading text | Not measured | 1241 | Only Grok 4.7 measured |
| LMArena Vision: creative writing | Not measured | 1217 | Only Grok 4.7 measured |
| Neither model has a result on the other 15 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-3.5 Turbo | Grok 4.7 | 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 | SpaceXAI Grok 4.7 |
|---|---|---|
| Maker | OpenAI | xAI |
| Weights | No public weights listed | No public weights listed |
| Released | May 28, 2023 | September 21, 2026 |
| Context window | 16K | 500K |
| Input $/Mtok | $0.50 | $2.00 |
| Output $/Mtok | $1.50 | $6.00 |
| Coding index | Not benchmarked | 66.7 |
| Independent measurements behind it | 0 | 5 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-3.5 Turbo better than Grok 4.7 for coding?
Only Grok 4.7 has a coding score, 66.7 on the Vibe Coding Index; GPT-3.5 Turbo has none, so the two cannot be ranked on coding. Pick GPT-3.5 Turbo for output tokens 4.0x cheaper ($1.50 vs $6.00 per million).
Which is cheaper, GPT-3.5 Turbo or Grok 4.7?
GPT-3.5 Turbo costs $0.50 per million input tokens and $1.50 per million output tokens; Grok 4.7 costs $2.00 and $6.00. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-3.5 Turbo or Grok 4.7?
Grok 4.7, with 500K tokens against 16K.
How many benchmarks is the GPT-3.5 Turbo vs Grok 4.7 comparison based on?
4 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 Grok 4.7's on 5. Where only one model has a result, the page says so instead of naming a winner.