Head-to-head · multimodal vs multimodal

Doubao 1.5 Pro Pro vs MiniMax-M2: which model should you choose?

We compared Doubao 1.5 Pro Pro and MiniMax-M2 on price, context window and 12 benchmarks. MiniMax-M2 has the stronger average benchmark score; MiniMax-M2 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
MiniMax

MiniMax-M2

MiniMax-M2 is a multimodal model from MiniMax. It offers a 200,000-token context window, costs $5.19 per million input tokens and $22.73 per million output tokens, and averages 80.6 across the index's benchmark suite.

Input
$5.19 / 1M
Output
$22.73 / 1M
Context
200,000
Avg score
80.6
Open weights
Yes
Full MiniMax-M2 page

Specification comparison

SpecDoubao 1.5 Pro ProMiniMax-M2Edge
Input price / 1M$14.10$5.19B
Output price / 1M$54.74$22.73B
Context window128,000200,000B
Max output8,19265,536B
Average score80.280.6B
Arena Elo1443.41423.8A
Open weightsNoYesB

Benchmark comparison

Doubao 1.5 Pro Pro wins 6, MiniMax-M2 wins 6, and 0 benchmarks are tied. The table shows the modelled score for each model and the gap.

BenchmarkDoubao 1.5 Pro ProMiniMax-M2GapWinner
MMLU-Pro80.281.81.6MiniMax-M2
GPQA Diamond74.575.40.9MiniMax-M2
SWE-bench Verified71.269.91.3Doubao 1.5 Pro Pro
HumanEval84.488.03.6MiniMax-M2
MATH-50085.482.33.1Doubao 1.5 Pro Pro
AIME 202577.778.10.4MiniMax-M2
LiveCodeBench71.673.41.8MiniMax-M2
IFEval87.886.11.7Doubao 1.5 Pro Pro
TruthfulQA84.683.51.1Doubao 1.5 Pro Pro
HellaSwag87.290.43.2MiniMax-M2
MMMU78.178.00.1Doubao 1.5 Pro Pro
Arena Elo1443.41423.819.6Doubao 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 MiniMax-M2 costs about $9.57. MiniMax-M2 is roughly 61% 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.

MiniMax-M2 has the larger context window at 200,000 tokens, compared with 128,000 for Doubao 1.5 Pro Pro. That matters for long documents, large codebases and multi-step agent traces.

Verdict

Across 12 shared benchmarks, Doubao 1.5 Pro Pro wins 6, MiniMax-M2 wins 6, and 0 are tied. On the index average, MiniMax-M2 leads Doubao 1.5 Pro Pro by 0.4 points (80.6 versus 80.2).

The price picture favours MiniMax-M2. The context picture favours MiniMax-M2. 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 MiniMax-M2 for quality-sensitive work, and check whether its price holds at your expected volume before committing.

Choose Doubao 1.5 Pro Pro if

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

Choose MiniMax-M2 if

  • You want the higher average benchmark score in this index.
  • Unit cost matters and you want the cheaper blended price.
  • You need the larger 200,000-token context window.
  • You need the larger 65,536-token output limit.

FAQ

Is Doubao 1.5 Pro Pro better than MiniMax-M2?

On the index average, MiniMax-M2 leads Doubao 1.5 Pro Pro by 0.4 points (80.6 versus 80.2). The better choice depends on price, context and your task. Doubao 1.5 Pro Pro wins 6 benchmarks, MiniMax-M2 wins 6.

Which is cheaper, Doubao 1.5 Pro Pro or MiniMax-M2?

MiniMax-M2 is cheaper on a blended 3:1 basis at about $9.57 per million tokens, versus $24.26 for Doubao 1.5 Pro Pro.

Which has the larger context window?

MiniMax-M2 has the larger context window at 200,000 tokens. Doubao 1.5 Pro Pro has 128,000 tokens.

Are these models open weights?

Doubao 1.5 Pro Pro is proprietary; MiniMax-M2 is open weights.

Which should I choose for production?

If you need a single default, start with MiniMax-M2 for quality-sensitive work, and check whether its price holds at your expected volume before committing.

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