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GPT-3.5 Turbo Instruct vs Extract

Updated October 21, 2026; no benchmark has tested both models yet.

GPT-3.5 Turbo InstructOpenAI
Coding
No data
Overall
No data
Output $/M
$2.00
S ExtractScaledown
Coding
No data
Overall
No data
Output $/M
No data
vs 4K vs 1M context window. Extract fits 244.2x more.

GPT-3.5 Turbo Instruct or Extract: which to pick

Neither model has a coding score yet, so the two cannot be ranked on coding.

Compare them on price, context and the boards below.

No benchmark has tested both yet. GPT-3.5 Turbo Instruct has results on METR time horizons; Extract has none yet. 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.

At a glance

Coding index
GPT-3.5 Turbo Instruct not benchmarked, Extract 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 Instruct $2.00 against Extract Free per million output tokens.
Context window
GPT-3.5 Turbo Instruct takes 4K tokens, Extract 1M.

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.

Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
Agentic work benchmarks for GPT-3.5 Turbo Instruct and Extract
BenchmarkGPT-3.5 Turbo InstructExtractLeader
METR time horizons21.5%Not measuredOnly GPT-3.5 Turbo Instruct measured
Neither model has a result on the other 40 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 Instruct$0.0025Fits in one request
Extract$0.0000Fits in one request

Extract costs less

Repository review

50K input + 3K output tokens

GPT-3.5 Turbo Instruct$0.081Exceeds the context window
Extract$0.0020Fits in one request

Extract costs less

Agent loop

200K input + 10K output tokens

GPT-3.5 Turbo Instruct$0.320Exceeds the context window
Extract$0.0080Fits in one request

Extract 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.

Specifications of GPT-3.5 Turbo Instruct and Extract
SpecificationOpenAI GPT-3.5 Turbo InstructScaleDown Extract
MakerOpenAIScaledown
WeightsNo public weights listedNo public weights listed
ReleasedSeptember 28, 2023October 13, 2026
Context window4K1M
Input $/Mtok$1.50$0.04
Output $/Mtok$2.00Free
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-3.5 Turbo Instruct better than Extract for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Compare them on price, context and the boards below.

Which is cheaper, GPT-3.5 Turbo Instruct or Extract?

GPT-3.5 Turbo Instruct costs $1.50 per million input tokens and $2.00 per million output tokens; Extract costs $0.04 and Free. Cost per solved task is known for neither of them.

Which has the bigger context window, GPT-3.5 Turbo Instruct or Extract?

Extract, with 1M tokens against 4K.

Has any benchmark tested both GPT-3.5 Turbo Instruct and Extract?

No benchmark has tested both yet. GPT-3.5 Turbo Instruct has results on METR time horizons; Extract has none yet. Compare them on price and context instead. Data as of October 21, 2026.

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