GPT-4 Turbo vs Sonar
Sonar leads GPT-4 Turbo on the Artificial Analysis Intelligence Index, 7.7 to 7.0, and Sonar costs 30.0x less per output token ($1.00 vs $30.00 per million). Updated October 21, 2026; 4 benchmarks have a result for both.
GPT-4 Turbo or Sonar: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick GPT-4 Turbo for a larger context window (128K against 127K tokens) and work measured by LiveCodeBench (Artificial Analysis run) or AA Intelligence Index, where it leads.
- Shared results
- 4
- GPT-4 Turbo only
- 38
- Sonar only
- 1
- Like-for-like categories
- 4 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
Sonar
Sonar leads, 7.7 against 7.0.
Same board, both measured
Long documents
Listed context window
GPT-4 Turbo
GPT-4 Turbo takes 128K tokens against 127K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Sonar
GPT-4 Turbo $0.025, Sonar $0.0015 per turn.
List prices
At a glance
- Coding index
- GPT-4 Turbo not benchmarked, Sonar not benchmarked.
- Widest category
- Reasoning, 1.8 points apart on average over 1 shared benchmark.
- Widest single gap
- Humanity's Last Exam (Artificial Analysis run): GPT-4 Turbo 3.1% against Sonar 4.9%, 1.8 points apart on a 0 to 100 scale.
- Output price
- GPT-4 Turbo $30.00 against Sonar $1.00 per million output tokens, 30.0x apart.
- Context window
- GPT-4 Turbo takes 128K tokens, Sonar 127K.
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-4 Turbo | Bars | Sonar | Ties |
|---|---|---|---|---|
| Coding | 0 | 1 | ||
| Intelligence | 0 | 1 | ||
| Reasoning | 0 | 1 | ||
| Knowledge | 1 | 0 | ||
| All shared boards | 1 | 3 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
| Benchmark | GPT-4 Turbo | Sonar | Leader |
|---|---|---|---|
| AA Coding Index | 21.5 | Not measured | Only GPT-4 Turbo measured |
| LiveCodeBench (Artificial Analysis run) | 29.1% | 29.5% | Sonar |
| LMArena Text: coding | 1268 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: software and IT | 1267 | Not measured | Only GPT-4 Turbo measured |
| Neither model has a result on the other 35 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-4 Turbo | Sonar | Leader |
|---|---|---|---|
| AA Intelligence Index | 7.0 | 7.7 | Sonar |
| Epoch Capabilities Index | 127.3 | Not measured | Only GPT-4 Turbo measured |
Agentic workNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-4 Turbo | Sonar | Leader |
|---|---|---|---|
| Neither model has a result on 41 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-4 Turbo | Sonar | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 47.1% | Only Sonar measured |
| Humanity's Last Exam (Artificial Analysis run) | 3.1% | 4.9% | Sonar |
| LMArena Text: hard prompts | 1251 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: expert | 1223 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: hard prompts in English | 1266 | Not measured | Only GPT-4 Turbo measured |
| Neither model has a result on the other 17 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GPT-4 Turbo | Sonar | Leader |
|---|---|---|---|
| LMArena Text: math | 1272 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: mathematical work | 1268 | Not measured | Only GPT-4 Turbo measured |
| Neither model has a result on the other 11 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-4 Turbo | Sonar | Leader |
|---|---|---|---|
| LegalBench (Vals AI) | 80.5% | Not measured | Only GPT-4 Turbo measured |
| MedQA (Vals AI) | 82.0% | Not measured | Only GPT-4 Turbo measured |
| MMLU Pro (Artificial Analysis run) | 69.4% | 68.9% | GPT-4 Turbo |
| MMLU | 81.3% | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: science | 1256 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: medicine and healthcare | 1239 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: legal and government | 1265 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: business and finance | 1222 | Not measured | Only GPT-4 Turbo 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-4 Turbo | Sonar | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index22 boards, none shared
| Benchmark | GPT-4 Turbo | Sonar | Leader |
|---|---|---|---|
| DTBench | 61.6% | Not measured | Only GPT-4 Turbo measured |
| LMCA | 9.8% | Not measured | Only GPT-4 Turbo measured |
| LMArena Text | 1272 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: instruction following | 1249 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: creative writing | 1268 | Not measured | Only GPT-4 Turbo measured |
| LMArena Vision | 1090 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: English | 1291 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: non-English | 1245 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: Chinese | 1242 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: German | 1259 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: Japanese | 1194 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: Korean | 1187 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: French | 1276 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: Spanish | 1260 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: Russian | 1259 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: Polish | 1302 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: multi-turn | 1267 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: longer queries | 1254 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: writing and language | 1279 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: entertainment and media | 1258 | Not measured | Only GPT-4 Turbo measured |
| LMArena Vision: English | 1097 | Not measured | Only GPT-4 Turbo measured |
| LMArena Vision: Chinese | 1045 | Not measured | Only GPT-4 Turbo measured |
| Neither model has a result on the other 24 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-4 Turbo | Sonar | 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
Sonar costs less
Repository review
50K input + 3K output tokens
Sonar costs less
Agent loop
200K input + 10K output tokens
Sonar 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-4 Turbo | Perplexity Sonar |
|---|---|---|
| Maker | OpenAI | Perplexity |
| Weights | No public weights listed | No public weights listed |
| Released | April 9, 2024 | January 27, 2025 |
| Context window | 128K | 127K |
| Input $/Mtok | $10.00 | $1.00 |
| Output $/Mtok | $30.00 | $1.00 |
| 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-4 Turbo better than Sonar for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-4 Turbo for a larger context window (128K against 127K tokens) and work measured by LiveCodeBench (Artificial Analysis run) or AA Intelligence Index, where it leads.
Which is cheaper, GPT-4 Turbo or Sonar?
GPT-4 Turbo costs $10.00 per million input tokens and $30.00 per million output tokens; Sonar costs $1.00 and $1.00. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-4 Turbo or Sonar?
GPT-4 Turbo, with 128K tokens against 127K.
How many benchmarks is the GPT-4 Turbo vs Sonar comparison based on?
4 benchmarks have a result for both models as of October 21, 2026. GPT-4 Turbo's coding index rests on 0 independent benchmarks and Sonar's on 0. Where only one model has a result, the page says so instead of naming a winner.