GPT-3.5 Turbo 16k vs GPT-5.2 Pro
GPT-3.5 Turbo 16k costs 42.0x less per output token than GPT-5.2 Pro ($4.00 vs $168.00 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
- $168.00
GPT-3.5 Turbo 16k or GPT-5.2 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 42.0x cheaper ($4.00 vs $168.00 per million).
No benchmark has tested both yet. GPT-3.5 Turbo 16k has none yet; GPT-5.2 Pro on Epoch Capabilities Index, ARC-AGI and ARC-AGI-2. 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
Long documents
Listed context window
GPT-5.2 Pro
GPT-5.2 Pro takes 400K 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, GPT-5.2 Pro $0.105 per turn.
List prices
At a glance
- Coding index
- GPT-3.5 Turbo 16k not benchmarked, GPT-5.2 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 GPT-5.2 Pro $168.00 per million output tokens, 42.0x apart.
- Context window
- GPT-3.5 Turbo 16k takes 16K tokens, GPT-5.2 Pro 400K.
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.
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | GPT-3.5 Turbo 16k | GPT-5.2 Pro | Leader |
|---|---|---|---|
| Epoch Capabilities Index | Not measured | 156.3 | Only GPT-5.2 Pro measured |
| Neither model has a result on the other 1 board here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index4 boards measured
| Benchmark | GPT-3.5 Turbo 16k | GPT-5.2 Pro | Leader |
|---|---|---|---|
| ARC-AGI | Not measured | 90.5% | Only GPT-5.2 Pro measured |
| ARC-AGI-2 | Not measured | 54.2% | Only GPT-5.2 Pro measured |
| SimpleBench | Not measured | 57.4% | Only GPT-5.2 Pro measured |
| Chess puzzles | Not measured | 60.0% | Only GPT-5.2 Pro measured |
| Neither model has a result on the other 19 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | GPT-3.5 Turbo 16k | GPT-5.2 Pro | Leader |
|---|---|---|---|
| FrontierMath, tiers 1 to 3 | Not measured | 74.0% | Only GPT-5.2 Pro measured |
| FrontierMath, tier 4 | Not measured | 46.0% | Only GPT-5.2 Pro measured |
| Neither model has a result on the other 12 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | GPT-3.5 Turbo 16k | GPT-5.2 Pro | Leader |
|---|---|---|---|
| PRBench Finance | Not measured | 46.3% | Only GPT-5.2 Pro measured |
| PRBench Legal | Not measured | 45.4% | Only GPT-5.2 Pro measured |
| Neither model has a result on the other 18 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 | OpenAI GPT-5.2 Pro |
|---|---|---|
| Maker | OpenAI | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | August 28, 2023 | December 10, 2025 |
| Context window | 16K | 400K |
| Input $/Mtok | $3.00 | $21.00 |
| Output $/Mtok | $4.00 | $168.00 |
| 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 GPT-5.2 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 42.0x cheaper ($4.00 vs $168.00 per million).
Which is cheaper, GPT-3.5 Turbo 16k or GPT-5.2 Pro?
GPT-3.5 Turbo 16k costs $3.00 per million input tokens and $4.00 per million output tokens; GPT-5.2 Pro costs $21.00 and $168.00. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-3.5 Turbo 16k or GPT-5.2 Pro?
GPT-5.2 Pro, with 400K tokens against 16K.
Has any benchmark tested both GPT-3.5 Turbo 16k and GPT-5.2 Pro?
No benchmark has tested both yet. GPT-3.5 Turbo 16k has none yet; GPT-5.2 Pro on Epoch Capabilities Index, ARC-AGI and ARC-AGI-2. Compare them on price and context instead. Data as of October 22, 2026.