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Command R7B (12-2024) vs GPT-3.5 Turbo Instruct

Command R7B (12-2024) costs 13.3x less per output token than GPT-3.5 Turbo Instruct ($0.15 vs $2.00 per million). Updated October 22, 2026; no benchmark has tested both models yet.

Command R7B (12-2024)Cohere
Coding
No data
Overall
No data
Output $/M
$0.15
GPT-3.5 Turbo InstructOpenAI
Coding
No data
Overall
No data
Output $/M
$2.00
vs $0.15 vs $2.00 per 1M output tokens. Command R7B (12-2024) is 13.3x cheaper.

Command R7B (12-2024) 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 Command R7B (12-2024) for output tokens 13.3x cheaper ($0.15 vs $2.00 per million) and a larger context window (128K against 4K tokens).

No benchmark has tested both yet. Command R7B (12-2024) has results on Berkeley Function Calling Leaderboard (BFCL); 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
Command R7B (12-2024) 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
Command R7B (12-2024) $0.15 against GPT-3.5 Turbo Instruct $2.00 per million output tokens, 13.3x apart.
Context window
Command R7B (12-2024) 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 index2 boards measured
Agentic work benchmarks for Command R7B (12-2024) and GPT-3.5 Turbo Instruct
BenchmarkCommand R7B (12-2024)GPT-3.5 Turbo InstructLeader
METR time horizonsNot measured21.5%Only GPT-3.5 Turbo Instruct measured
Berkeley Function Calling Leaderboard (BFCL)32.1%Not measuredOnly Command R7B (12-2024) measured
Neither model has a result on the other 39 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

Command R7B (12-2024)$0.0001Fits in one request
GPT-3.5 Turbo Instruct$0.0025Fits in one request

Command R7B (12-2024) costs less

Repository review

50K input + 3K output tokens

Command R7B (12-2024)$0.0023Fits in one request
GPT-3.5 Turbo Instruct$0.081Exceeds the context window

Command R7B (12-2024) costs less

Agent loop

200K input + 10K output tokens

Command R7B (12-2024)$0.0090Exceeds the context window
GPT-3.5 Turbo Instruct$0.320Exceeds the context window

Command R7B (12-2024) 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 Command R7B (12-2024) and GPT-3.5 Turbo Instruct
SpecificationCohere Command R7B (12-2024)OpenAI GPT-3.5 Turbo Instruct
MakerCohereOpenAI
WeightsNo public weights listedNo public weights listed
ReleasedDecember 14, 2024September 28, 2023
Context window128K4K
Input $/Mtok$0.0375$1.50
Output $/Mtok$0.15$2.00
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Command R7B (12-2024) 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 Command R7B (12-2024) for output tokens 13.3x cheaper ($0.15 vs $2.00 per million) and a larger context window (128K against 4K tokens).

Which is cheaper, Command R7B (12-2024) or GPT-3.5 Turbo Instruct?

Command R7B (12-2024) costs $0.0375 per million input tokens and $0.15 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, Command R7B (12-2024) or GPT-3.5 Turbo Instruct?

Command R7B (12-2024), with 128K tokens against 4K.

Has any benchmark tested both Command R7B (12-2024) and GPT-3.5 Turbo Instruct?

No benchmark has tested both yet. Command R7B (12-2024) has results on Berkeley Function Calling Leaderboard (BFCL); 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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