Google vs Groq · synced 2026-08-11

gemini-3.5-flash vs llama-3.1-8b-instant

llama-3.1-8b-instant is 30.0× cheaper on input than gemini-3.5-flash.

gemini-3.5-flash llama-3.1-8b-instant
Input / 1M $1.50 $0.05
Cached input / 1M $0.15
Output / 1M $9.00 $0.08
Context window 1M 128K
Max output 66K 8K
Provider Google Groq
Vision Yes 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: gemini-3.5-flash leads llama-3.1-8b-instant by 66.3 points on hard reasoning (GPQA Diamond), for 58.7× the price.

  1. Following instructions

    extraction, classification, sticking to a format

    IFBench
    gemini-3.5-flash76.3%
    llama-3.1-8b-instant28.6%

    gemini-3.5-flash +47.7

  2. Tool use

    multi-step agent work against real tools

    τ²-bench
    gemini-3.5-flash95.3%
    llama-3.1-8b-instant16.4%

    gemini-3.5-flash +78.9

  3. Hard reasoning

    graduate-level science and multi-step analysis

    GPQA Diamond
    gemini-3.5-flash92.2%
    llama-3.1-8b-instant25.9%

    gemini-3.5-flash +66.3

Averaged over the benchmarks both models sat, llama-3.1-8b-instant returns 411.0 points of pass rate per dollar of blended price against 26.1 — 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 coding score for one of these models, so that lens is 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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