Moonshot AI · multimodal · Released 2026-10-01

Kimi K1.5 Base: pricing, context window and benchmarks

Kimi K1.5 Base is a multimodal model from Moonshot AI. It offers a 65,536-token context window, costs $4.34 per million input tokens and $15.70 per million output tokens, and averages 77.4 across the index's benchmark suite.

codingvisionopen weightsmultimodal
Input price
$4.34
per 1M tokens
Output price
$15.70
per 1M tokens
Context
65,536
tokens
Avg score
77.4
rank #188 of 600
Arena Elo
1397.5
modelled
Max output
16,384
tokens

Pricing

Kimi K1.5 Base costs $4.34 per million input tokens and $15.70 per million output tokens. A blended 3:1 input-to-output mix works out to about $7.18 per million tokens. Cached input is listed at $0.60 per million tokens.

ItemPriceNotes
Input$4.34per 1M tokens
Output$15.70per 1M tokens
Cached input$0.60per 1M tokens
Blended 3:1$7.18estimate per 1M tokens
1M in + 1M out$20.04estimate

Benchmarks

Scores below are modelled estimates on a 0–100 scale. Use them to compare relative position, not as official vendor results.

BenchmarkScoreRankPercentileRelative
MMLU-Pro 78.2 237 61th
GPQA Diamond 74.3 160 73th
SWE-bench Verified 67.3 162 73th
HumanEval 82.2 181 70th
MATH-500 79.9 211 65th
AIME 2025 72.9 204 66th
LiveCodeBench 67.0 250 58th
IFEval 86.0 157 74th
TruthfulQA 81.2 149 75th
HellaSwag 85.8 223 63th
MMMU 76.3 133 78th
Arena Elo 1397.5 216 64th

What Kimi K1.5 Base is good for

Kimi K1.5 Base is tuned toward coding work. It is a reasonable candidate for code generation, review, debugging and repository-scale tasks, especially when paired with a retrieval layer. At $4.34 per million input tokens, it sits in the mid-range of the index, and the 65,536-token context window is enough for large files and multi-file diffs.

Strengths

  • Open weights make self-hosting, fine-tuning and data-residency review possible.
  • Accepts more than text, including image input where the provider supports it.
  • Coding benchmarks are a relative strength within its tier.

Trade-offs

  • No standout weakness in the indexed specifications, but real-world behaviour still needs testing.

How it compares

ModelProviderContextInput / 1MAvg score
ERNIE 4.0 Pro Baidu 200000 $12.58 77.5
Hunyuan-Turbo Reasoning Tencent 128000 $11.89 77.5
Hunyuan-Turbo Turbo Tencent 65536 $11.60 77.4
Kimi K1.5 Base Moonshot AI 65536 $4.34 77.4
Qwen3 Base Alibaba Cloud 65536 $4.33 77.4
Reka Core Reka AI 32768 $12.17 77.4

Browse all comparisons →

FAQ

How much does Kimi K1.5 Base cost?

Kimi K1.5 Base is listed at $4.34 per million input tokens and $15.70 per million output tokens. Cached input is $0.60 per million tokens. A blended 3:1 input-to-output mix is about $7.18 per million tokens.

What is the context window of Kimi K1.5 Base?

Kimi K1.5 Base has a context window of 65,536 tokens and can emit up to 16,384 output tokens per request in this index.

Is Kimi K1.5 Base open weights?

Yes. Kimi K1.5 Base is listed as an open-weight model under a open weights licence.

How does Kimi K1.5 Base score on benchmarks?

Kimi K1.5 Base averages 77.4 across the scored benchmarks in this index, ranking #188 of 600 models. Its strongest relative result is Arena Elo at 1397.5.

What is Kimi K1.5 Base best for?

Kimi K1.5 Base is tuned toward coding work. It is a reasonable candidate for code generation, review, debugging and repository-scale tasks, especially when paired with a retrieval layer. At $4.34 per million input tokens, it sits in the mid-range of the index, and the 65,536-token context window is enough for large files and multi-file diffs.

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