Cohere vs Groq · synced 2026-08-11

command-r vs llama-3.3-70b-versatile

command-r is 3.9× cheaper on input than llama-3.3-70b-versatile.

command-r llama-3.3-70b-versatile
Input / 1M $0.15 $0.59
Cached input / 1M
Output / 1M $0.60 $0.79
Context window 128K 128K
Max output 4K 33K
Provider Cohere Groq
Vision No No
Tool calling Yes Yes
Token count estimated estimated

Capability for the money

Independent measurement · Artificial Analysis · read 2026-08-11

Not the same tier: llama-3.3-70b-versatile leads command-r by 21.4 points on hard reasoning (GPQA Diamond), for 2.4× the price.

  1. Coding

    writing and fixing code

    LiveCodeBench
    command-r4.8%
    llama-3.3-70b-versatile28.8%

    llama-3.3-70b-versatile +24.0

  2. Hard reasoning

    graduate-level science and multi-step analysis

    GPQA Diamond
    command-r28.4%
    llama-3.3-70b-versatile49.8%

    llama-3.3-70b-versatile +21.4

Averaged over the benchmarks both models sat, command-r returns 63.2 points of pass rate per dollar of blended price against 61.4 — the ratio that decides whether the dearer model earns its rate.

Each figure is a pass rate: the share of that test set the model answered correctly, measured by a third party rather than self-reported by the lab. Rows are different tests of different difficulty, so compare a model against the other model, not one row against the next. No published following instructions or tool use score for one of these models, so those lenses are omitted. And a benchmark is not your workload — it narrows the shortlist, it does not pick for you.

Which to pick

List price is not production cost. Output length, cache hit rate, retries and task quality move the real number more than the headline rate does — price your own prompt on the token ledger before deciding.

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