Thinking Machines: Inkling (batch) vs Kimi K3 benchmark

Interactive Comparison Diagram

Recommended Workload Routing

Frequently Asked Questions

Which is better overall, Thinking Machines: Inkling (batch) or Kimi K3?

We do not have preference Elo for both models, so we do not declare an overall winner. Compare the metrics that exist.

Which is better at coding, Thinking Machines: Inkling (batch) or Kimi K3?

SWE-bench is missing for at least one model, so we do not rank coding from a single number.

Which is cheaper to run in production?

Thinking Machines: Inkling (batch) output tokens are $2.03/1M versus $15/1M. Input prices and retry rates still move the real bill.

Which is faster, Thinking Machines: Inkling (batch) or Kimi K3?

We do not have TTFT for both models.

Which has the larger context window?

Kimi K3 accepts 1M tokens versus 524k.

Can I self-host either model?

Neither model is marked open-weights here. You are comparing hosted APIs.

Are these scores from CompareLLM’s own evals?

No. V1 aggregates public leaderboards (and optional first-party latency pings). Each cell names its source and date. Read /methodology.

What does preference Elo mean on this page?

Preference Elo is a crowd vote from LMArena / Arena. People see two hidden answers and pick the one they like more. The model that wins more often gets a higher Elo. That means people preferred it — not that it passed a school test. It is not SWE-bench, not accuracy, and not a number we invent. Thinking Machines: Inkling (batch) and Kimi K3 Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.