Alternatives to Kimi K3

Moonshot AI LMArena 1475.9 $3.76/M on a balanced workload prices as of 2026-10-06

3 models are higher-scoring or cheaper, with neither dimension worse.

Of the 144 models carrying both an independent score and a published price at the same delivery mode, 9 score at least as high as Kimi K3 and cost no more under at least one listed workload, with at least one of those dimensions improved. 3 match or beat its recorded context, maximum output, input modes, tool use and extended reasoning. 6 have a recorded capability loss, named on every row.

Dominance is not a property of a model. It is a property of a model, a capability lens and a workload, and all three are named on every row. Scores are LMArena Elo, used under CC BY 4.0 from the official dataset; prices are blended per million tokens. A higher score is not a drop-in replacement.

This page is built only while a candidate improves score or price without worsening the other under a listed workload. When that comparison no longer holds, it is not generated.

Where it holds

WorkloadKimi K3 $/MRecorded capabilities preservedRecorded capability losses
Balanced$3.7635
Summarise$1.2332
Chat$5.5436
Code gen$8.0536
Agentic$2.3935

Workload mixes are defined on the methodology page. Cached input is priced at the cached rate, and reasoning tokens at the worse of the reasoning and output rates.

What you would be replacing

Intelligence1475.9
Context window1M
Max output943K
Input modestext, image, video
Tool useyes
Extended reasoningyes

Preserving recorded capabilities requires matching or beating these fields. Full record for Kimi K3, or check Kimi K3 against the whole catalogue.

Recorded capabilities preserved 3

Each option has a higher score or a lower price, with neither dimension worse under the listed workloads. It matches or beats Kimi K3 on recorded context, maximum output, input modes, tool use and extended reasoning.

#ModelIntelligence$/MHolds under
1Muse Spark 1.3 Meta1489.9 +14$2.00
  • Balanced −47%
  • Summarise −12%
  • Chat −62%
  • Code gen −63%
  • Agentic −56%
2Muse Spark 1.2 Meta1483.2 tie$2.00
  • Balanced −47%
  • Summarise −12%
  • Chat −62%
  • Code gen −63%
  • Agentic −56%
3Muse Spark 1.1 Meta1479.2 tie$2.00
  • Balanced −47%
  • Summarise −12%
  • Chat −62%
  • Code gen −63%
  • Agentic −56%

Alternatives with recorded capability losses 6

These improve score or price without worsening the other under the listed workloads, but reduce at least one recorded capability. Read the last column before switching.

ModelIntelligence$/MHolds underRecorded capability loss
MiMo-V2.6-Pro Xiaomi1491 +15.1$0.540
  • Balanced −86%
  • Summarise −73%
  • Chat −91%
  • Code gen −92%
  • Agentic −90%
  • 944K → 131K max output
Gemini 3.8 Flash Google1497 +21.1$3.00
  • Balanced −20%
  • Chat −37%
  • Code gen −38%
  • Agentic −33%
  • 944K → 66K max output
Gemini 3.7 Flash Google1487 +11.1$3.00
  • Balanced −20%
  • Chat −37%
  • Code gen −38%
  • Agentic −33%
  • 944K → 66K max output
Gemini 3.6 Flash Google1479.5 tie$1.50
  • Balanced −60%
  • Summarise −42%
  • Chat −68%
  • Code gen −69%
  • Agentic −67%
  • 944K → 66K max output
Gemini 3.5 Flash Google1477.7 tie$3.38
  • Balanced −10%
  • Chat −26%
  • Code gen −27%
  • Agentic −24%
  • 944K → 66K max output
Gemini 3.1 Pro Preview Google1480.2 tie$5.46 chat
  • Chat −1%
  • Code gen −2%
  • 944K → 66K max output

What this compares, and what it leaves out

  • Quality is LMArena Elo, used under CC BY 4.0 from the official dataset. The 95% confidence interval on a difference between two scores is about ±10.47 points, so a gap smaller than that is marked tie rather than an improvement — see significance bands.
  • 204 further models at this delivery mode carry a price but no independent score. They are absent from the comparison in both directions — unrated is not a zero, and an unmeasured model is neither an alternative nor a worse buy.
  • Retired models are never offered as an alternative, and a model only competes against its own delivery mode: batch trades latency for price, so it is not a like-for-like swap.
  • Nothing here measures latency, throughput, rate limits or how a model behaves on your prompts. Two models with the same index score are not interchangeable.
  • Models with no higher-scoring or cheaper alternative that is no worse on the other axis are on the value frontier. Models with such an alternative are listed here.
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