GPT-3.5 Turbo Instruct vs Sakana Namazu

GPT-3.5 Turbo Instruct costs 2.0x less per output token than Sakana Namazu ($2.00 vs $4.00 per million). Updated October 23, 2026; no benchmark has tested both models yet.

Replace GPT-3.5 Turbo Instruct Replace Sakana Namazu

GPT-3.5 Turbo InstructOpenAI

Coding: No data
Overall: No data
Output $/M: $2.00

Sakana NamazuSakana

Coding: No data
Overall: No data
Output $/M: $4.00

vs $2.00 vs $4.00 per 1M output tokens. GPT-3.5 Turbo Instruct is 2.0x cheaper.

GPT-3.5 Turbo Instruct or Sakana Namazu: which to pick

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

Pick GPT-3.5 Turbo Instruct for output tokens 2.0x cheaper ($2.00 vs $4.00 per million).

Model AGPT-3.5 Turbo InstructOpenAINot benchmarkedNo coding benchmarkNo cost per solved task Model BSakana NamazuSakanaNot benchmarkedNo coding benchmarkNo cost per solved task

No benchmark has tested both yet. GPT-3.5 Turbo Instruct has results on METR time horizons; Sakana Namazu 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.

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
Sakana Namazu
Sakana Namazu takes 262K tokens against 4K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-3.5 Turbo Instruct
GPT-3.5 Turbo Instruct $0.0025, Sakana Namazu $0.0029 per turn.
List prices

At a glance

Coding index: GPT-3.5 Turbo Instruct not benchmarked, Sakana Namazu 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 Sakana Namazu $4.00 per million output tokens, 2.0x apart.
Context window: GPT-3.5 Turbo Instruct takes 4K tokens, Sakana Namazu 262K.

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 Sakana Namazu
Benchmark	GPT-3.5 Turbo Instruct	Sakana Namazu	Leader
METR time horizons	21.5%	Not measured	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

GPT-3.5 Turbo Instruct$0.0025Fits in one request

Sakana Namazu$0.0029Fits in one request

GPT-3.5 Turbo Instruct costs less

Repository review

50K input + 3K output tokens

GPT-3.5 Turbo Instruct$0.081Exceeds the context window

Sakana Namazu$0.059Fits in one request

Sakana Namazu costs less

Agent loop

200K input + 10K output tokens

GPT-3.5 Turbo Instruct$0.320Exceeds the context window

Sakana Namazu$0.230Fits in one request

Sakana Namazu 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 Sakana Namazu
Specification	OpenAI GPT-3.5 Turbo Instruct	Sakana Namazu
Maker	OpenAI	Sakana
Weights	No public weights listed	No public weights listed
Released	September 28, 2023	August 11, 2026
Context window	4K	262K
Input $/Mtok	$1.50	$0.95
Output $/Mtok	$2.00	$4.00
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 Instruct better than Sakana Namazu for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-3.5 Turbo Instruct for output tokens 2.0x cheaper ($2.00 vs $4.00 per million).

Which is cheaper, GPT-3.5 Turbo Instruct or Sakana Namazu?

GPT-3.5 Turbo Instruct costs $1.50 per million input tokens and $2.00 per million output tokens; Sakana Namazu costs $0.95 and $4.00. Cost per solved task is known for neither of them.

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

Sakana Namazu, with 262K tokens against 4K.

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

No benchmark has tested both yet. GPT-3.5 Turbo Instruct has results on METR time horizons; Sakana Namazu has none yet. Compare them on price and context instead. Data as of October 23, 2026.