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Uncensored vs GPT-3.5 Turbo Instruct

Uncensored costs 2.2x less per output token than GPT-3.5 Turbo Instruct ($0.90 vs $2.00 per million). Updated October 22, 2026; no benchmark has tested both models yet.

C UncensoredCognitive Computations
Coding
No data
Overall
No data
Output $/M
$0.90
GPT-3.5 Turbo InstructOpenAI
Coding
No data
Overall
No data
Output $/M
$2.00
vs $0.90 vs $2.00 per 1M output tokens. Uncensored is 2.2x cheaper.

Uncensored or GPT-3.5 Turbo Instruct: which to pick

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

Pick Uncensored for output tokens 2.2x cheaper ($0.90 vs $2.00 per million) and a larger context window (128K against 4K tokens).

No benchmark has tested both yet. Uncensored has none yet; GPT-3.5 Turbo Instruct on METR time horizons. 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
Uncensored not benchmarked, GPT-3.5 Turbo Instruct 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
Uncensored $0.90 against GPT-3.5 Turbo Instruct $2.00 per million output tokens, 2.2x apart.
Context window
Uncensored takes 128K tokens, GPT-3.5 Turbo Instruct 4K.

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 Uncensored and GPT-3.5 Turbo Instruct
BenchmarkUncensoredGPT-3.5 Turbo InstructLeader
METR time horizonsNot measured21.5%Only GPT-3.5 Turbo Instruct measured
Neither model has a result on the other 41 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

Uncensored$0.0006Fits in one request
GPT-3.5 Turbo Instruct$0.0025Fits in one request

Uncensored costs less

Repository review

50K input + 3K output tokens

Uncensored$0.013Fits in one request
GPT-3.5 Turbo Instruct$0.081Exceeds the context window

Uncensored costs less

Agent loop

200K input + 10K output tokens

Uncensored$0.049Exceeds the context window
GPT-3.5 Turbo Instruct$0.320Exceeds the context window

Uncensored 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 Uncensored and GPT-3.5 Turbo Instruct
SpecificationVenice UncensoredOpenAI GPT-3.5 Turbo Instruct
MakerCognitive ComputationsOpenAI
WeightsOpen weightsNo public weights listed
ReleasedJuly 9, 2025September 28, 2023
Context window128K4K
Input $/Mtok$0.20$1.50
Output $/Mtok$0.90$2.00
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

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

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Uncensored for output tokens 2.2x cheaper ($0.90 vs $2.00 per million) and a larger context window (128K against 4K tokens).

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

Uncensored costs $0.20 per million input tokens and $0.90 per million output tokens; GPT-3.5 Turbo Instruct costs $1.50 and $2.00. Cost per solved task is known for neither of them.

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

Uncensored, with 128K tokens against 4K.

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

No benchmark has tested both yet. Uncensored has none yet; GPT-3.5 Turbo Instruct on METR time horizons. Compare them on price and context instead. Data as of October 22, 2026.

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