GPT-3.5 Turbo 16k vs Sonar Pro
GPT-3.5 Turbo 16k costs 3.8x less per output token than Sonar Pro ($4.00 vs $15.00 per million). Updated October 22, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $4.00
- Coding
- No data
- Overall
- No data
- Output $/M
- $15.00
GPT-3.5 Turbo 16k or Sonar Pro: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick GPT-3.5 Turbo 16k for output tokens 3.8x cheaper ($4.00 vs $15.00 per million).
No benchmark has tested both yet. GPT-3.5 Turbo 16k has none yet; Sonar Pro on LiveCodeBench (Artificial Analysis run), AA Intelligence Index and GPQA Diamond (Artificial Analysis run). Compare them on price and context instead.
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 Sonar Pro has a AA Intelligence Index result, 7.6.
Directional only
Long documents
Listed context window
Sonar Pro
Sonar Pro takes 200K tokens against 16K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-3.5 Turbo 16k
GPT-3.5 Turbo 16k $0.0050, Sonar Pro $0.011 per turn.
List prices
At a glance
- Coding index
- GPT-3.5 Turbo 16k not benchmarked, Sonar Pro not benchmarked.
- Widest category
- None yet: no category has been tested on both models.
- Widest single gap
- None yet: no benchmark has tested both models.
- Output price
- GPT-3.5 Turbo 16k $4.00 against Sonar Pro $15.00 per million output tokens, 3.8x apart.
- Context window
- GPT-3.5 Turbo 16k takes 16K tokens, Sonar Pro 200K.
Benchmark by benchmark
Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.
CodingDirectional onlySix of these boards feed the Vibe Coding Index1 board measured
| Benchmark | GPT-3.5 Turbo 16k | Sonar Pro | Leader |
|---|---|---|---|
| LiveCodeBench (Artificial Analysis run) | Not measured | 27.5% | Only Sonar Pro measured |
| Neither model has a result on the other 38 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | GPT-3.5 Turbo 16k | Sonar Pro | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 7.6 | Only Sonar Pro measured |
| Neither model has a result on the other 1 board here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | GPT-3.5 Turbo 16k | Sonar Pro | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 57.8% | Only Sonar Pro measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 6.6% | Only Sonar Pro measured |
| Neither model has a result on the other 20 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | GPT-3.5 Turbo 16k | Sonar Pro | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | Not measured | 75.5% | Only Sonar Pro measured |
| Neither model has a result on the other 17 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 16k costs less
Repository review
50K input + 3K output tokens
GPT-3.5 Turbo 16k costs less
Agent loop
200K input + 10K output tokens
GPT-3.5 Turbo 16k 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 16k | Perplexity Sonar Pro |
|---|---|---|
| Maker | OpenAI | Perplexity |
| Weights | No public weights listed | No public weights listed |
| Released | August 28, 2023 | March 7, 2025 |
| Context window | 16K | 200K |
| Input $/Mtok | $3.00 | $3.00 |
| Output $/Mtok | $4.00 | $15.00 |
| 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 16k better than Sonar Pro for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-3.5 Turbo 16k for output tokens 3.8x cheaper ($4.00 vs $15.00 per million).
Which is cheaper, GPT-3.5 Turbo 16k or Sonar Pro?
GPT-3.5 Turbo 16k costs $3.00 per million input tokens and $4.00 per million output tokens; Sonar Pro costs $3.00 and $15.00. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-3.5 Turbo 16k or Sonar Pro?
Sonar Pro, with 200K tokens against 16K.
Has any benchmark tested both GPT-3.5 Turbo 16k and Sonar Pro?
No benchmark has tested both yet. GPT-3.5 Turbo 16k has none yet; Sonar Pro on LiveCodeBench (Artificial Analysis run), AA Intelligence Index and GPQA Diamond (Artificial Analysis run). Compare them on price and context instead. Data as of October 22, 2026.