Head-to-head · multimodal vs multimodal

Doubao 1.5 Pro Pro vs Kimi K1.5 Chat: which model should you choose?

We compared Doubao 1.5 Pro Pro and Kimi K1.5 Chat on price, context window and 12 benchmarks. Doubao 1.5 Pro Pro and Kimi K1.5 Chat are effectively tied on the index average; Kimi K1.5 Chat is cheaper on a blended 3:1 basis.

ByteDance

Doubao 1.5 Pro Pro

Doubao 1.5 Pro Pro is a multimodal model from ByteDance. It offers a 128,000-token context window, costs $14.10 per million input tokens and $54.74 per million output tokens, and averages 80.2 across the index's benchmark suite.

Input
$14.10 / 1M
Output
$54.74 / 1M
Context
128,000
Avg score
80.2
Open weights
No
Full Doubao 1.5 Pro Pro page
Moonshot AI

Kimi K1.5 Chat

Kimi K1.5 Chat is a multimodal model from Moonshot AI. It offers a 128,000-token context window, costs $5.11 per million input tokens and $26.59 per million output tokens, and averages 80.2 across the index's benchmark suite.

Input
$5.11 / 1M
Output
$26.59 / 1M
Context
128,000
Avg score
80.2
Open weights
Yes
Full Kimi K1.5 Chat page

Specification comparison

SpecDoubao 1.5 Pro ProKimi K1.5 ChatEdge
Input price / 1M$14.10$5.11B
Output price / 1M$54.74$26.59B
Context window128,000128,000Tie
Max output8,19232,768B
Average score80.280.2Tie
Arena Elo1443.41422.6A
Open weightsNoYesB

Benchmark comparison

Doubao 1.5 Pro Pro wins 6, Kimi K1.5 Chat wins 5, and 1 benchmarks are tied. The table shows the modelled score for each model and the gap.

BenchmarkDoubao 1.5 Pro ProKimi K1.5 ChatGapWinner
MMLU-Pro80.281.31.1Kimi K1.5 Chat
GPQA Diamond74.578.13.6Kimi K1.5 Chat
SWE-bench Verified71.269.91.3Doubao 1.5 Pro Pro
HumanEval84.484.30.1Doubao 1.5 Pro Pro
MATH-50085.481.73.7Doubao 1.5 Pro Pro
AIME 202577.781.43.7Kimi K1.5 Chat
LiveCodeBench71.675.74.1Kimi K1.5 Chat
IFEval87.888.20.4Kimi K1.5 Chat
TruthfulQA84.680.34.3Doubao 1.5 Pro Pro
HellaSwag87.287.20.0Tie
MMMU78.173.64.5Doubao 1.5 Pro Pro
Arena Elo1443.41422.620.8Doubao 1.5 Pro Pro

Price analysis

On a blended 3:1 input-to-output basis, Doubao 1.5 Pro Pro costs about $24.26 per million tokens and Kimi K1.5 Chat costs about $10.48. Kimi K1.5 Chat is roughly 57% cheaper than Doubao 1.5 Pro Pro. At high volume, that gap compounds quickly, so price should carry real weight unless the quality difference is decisive.

Both models list a 128,000-token context window. That is enough for long documents, large codebases and multi-step agent traces.

Verdict

Across 12 shared benchmarks, Doubao 1.5 Pro Pro wins 6, Kimi K1.5 Chat wins 5, and 1 are tied. The two models are effectively tied on the index average at 80.2.

The price picture favours Kimi K1.5 Chat. The context picture is effectively a tie. Those two dimensions often matter more than a few benchmark points once a model is good enough for the task.

If you need a single default, start with Kimi K1.5 Chat if cost is the constraint and Doubao 1.5 Pro Pro if context is the constraint. Test both on a sample of your own traffic before committing.

Choose Doubao 1.5 Pro Pro if

  • You prefer ByteDance's tooling or already use it.

Choose Kimi K1.5 Chat if

  • Unit cost matters and you want the cheaper blended price.
  • You need the larger 32,768-token output limit.
  • You need open weights for self-hosting or fine-tuning.

FAQ

Is Doubao 1.5 Pro Pro better than Kimi K1.5 Chat?

The two models are effectively tied on the index average at 80.2. The better choice depends on price, context and your task. Doubao 1.5 Pro Pro wins 6 benchmarks, Kimi K1.5 Chat wins 5.

Which is cheaper, Doubao 1.5 Pro Pro or Kimi K1.5 Chat?

Kimi K1.5 Chat is cheaper on a blended 3:1 basis at about $10.48 per million tokens, versus $24.26 for Doubao 1.5 Pro Pro.

Which has the larger context window?

Both models list a 128,000-token context window.

Are these models open weights?

Doubao 1.5 Pro Pro is proprietary; Kimi K1.5 Chat is open weights.

Which should I choose for production?

If you need a single default, start with Kimi K1.5 Chat if cost is the constraint and Doubao 1.5 Pro Pro if context is the constraint. Test both on a sample of your own traffic before committing.

Related comparisons