kimi-k2-0905-preview vs llama-3.3-70b-versatile
kimi-k2-0905-preview and llama-3.3-70b-versatile are priced within 15% of each other on input.
| kimi-k2-0905-preview | llama-3.3-70b-versatile | |
|---|---|---|
| Input / 1M | $0.60 | $0.59 |
| Cached input / 1M | $0.15 | — |
| Output / 1M | $2.50 | $0.79 |
| Context window | 262K | 128K |
| Max output | 262K | 33K |
| Provider | Moonshot | Groq |
| Vision | No | No |
| Tool calling | Yes | Yes |
| Token count | estimated | estimated |
Capability for the money
Independent measurement · Artificial Analysis · read 2026-08-11Not the same tier: kimi-k2-0905-preview leads llama-3.3-70b-versatile by 46.8 points on tool use (τ²-bench), for 1.7× the price. They are level on following instructions (IFBench), so the premium only pays off on tool use work.
Following instructions
extraction, classification, sticking to a format
IFBenchllama-3.3-70b-versatile +5.4
Coding
writing and fixing code
LiveCodeBenchkimi-k2-0905-preview +32.2
Tool use
multi-step agent work against real tools
τ²-benchkimi-k2-0905-preview +46.8
Hard reasoning
graduate-level science and multi-step analysis
GPQA Diamondkimi-k2-0905-preview +26.9
Averaged over the benchmarks both models sat, llama-3.3-70b-versatile returns 59.5 points of pass rate per dollar of blended price against 58.8 — 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. And a benchmark is not your workload — it narrows the shortlist, it does not pick for you.
Which to pick
- Cheaper input: llama-3.3-70b-versatile
- Cheaper output: llama-3.3-70b-versatile
- Larger context: kimi-k2-0905-preview
- Better at following instructions: llama-3.3-70b-versatile (41.7% vs 47.1% on IFBench)
- Better at coding: kimi-k2-0905-preview (61.0% vs 28.8% on LiveCodeBench)
- Better at tool use: kimi-k2-0905-preview (73.4% vs 26.6% on τ²-bench)
- Better at hard reasoning: kimi-k2-0905-preview (76.7% vs 49.8% on GPQA Diamond)
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.
Related comparisons
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