Head-to-head · multimodal vs multimodal

MiniMax-M2 Instruct vs Sonar Pro Max: which model should you choose?

We compared MiniMax-M2 Instruct and Sonar Pro Max on price, context window and 12 benchmarks. Sonar Pro Max has the stronger average benchmark score; MiniMax-M2 Instruct is cheaper on a blended 3:1 basis.

MiniMax

MiniMax-M2 Instruct

MiniMax-M2 Instruct is a multimodal model from MiniMax. It offers a 128,000-token context window, costs $5.11 per million input tokens and $25.04 per million output tokens, and averages 79.4 across the index's benchmark suite.

Input
$5.11 / 1M
Output
$25.04 / 1M
Context
128,000
Avg score
79.4
Open weights
Yes
Full MiniMax-M2 Instruct page
Perplexity

Sonar Pro Max

Sonar Pro Max is a multimodal model from Perplexity. It offers a 128,000-token context window, costs $14.01 per million input tokens and $69.33 per million output tokens, and averages 81.1 across the index's benchmark suite.

Input
$14.01 / 1M
Output
$69.33 / 1M
Context
128,000
Avg score
81.1
Open weights
No
Full Sonar Pro Max page

Specification comparison

SpecMiniMax-M2 InstructSonar Pro MaxEdge
Input price / 1M$5.11$14.01A
Output price / 1M$25.04$69.33A
Context window128,000128,000Tie
Max output4,0964,096Tie
Average score79.481.1B
Arena Elo1442.21437.8A
Open weightsYesNoA

Benchmark comparison

MiniMax-M2 Instruct wins 4, Sonar Pro Max wins 8, and 0 benchmarks are tied. The table shows the modelled score for each model and the gap.

BenchmarkMiniMax-M2 InstructSonar Pro MaxGapWinner
MMLU-Pro82.183.71.6Sonar Pro Max
GPQA Diamond73.778.85.1Sonar Pro Max
SWE-bench Verified69.971.71.8Sonar Pro Max
HumanEval86.785.11.6MiniMax-M2 Instruct
MATH-50082.186.24.1Sonar Pro Max
AIME 202577.874.92.9MiniMax-M2 Instruct
LiveCodeBench71.175.74.6Sonar Pro Max
IFEval87.388.31.0Sonar Pro Max
TruthfulQA80.082.02.0Sonar Pro Max
HellaSwag88.588.00.5MiniMax-M2 Instruct
MMMU74.177.23.1Sonar Pro Max
Arena Elo1442.21437.84.4MiniMax-M2 Instruct

Price analysis

On a blended 3:1 input-to-output basis, MiniMax-M2 Instruct costs about $10.09 per million tokens and Sonar Pro Max costs about $27.84. MiniMax-M2 Instruct is roughly 64% cheaper than Sonar Pro Max. 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, MiniMax-M2 Instruct wins 4, Sonar Pro Max wins 8, and 0 are tied. On the index average, Sonar Pro Max leads MiniMax-M2 Instruct by 1.7 points (81.1 versus 79.4).

The price picture favours MiniMax-M2 Instruct. 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 Sonar Pro Max for quality-sensitive work and MiniMax-M2 Instruct for high-volume, well-scoped tasks. Run both on a sample of your own traffic before locking in a choice.

Choose MiniMax-M2 Instruct if

  • Unit cost matters and you want the cheaper blended price.
  • You need open weights for self-hosting or fine-tuning.

Choose Sonar Pro Max if

  • You want the higher average benchmark score in this index.

FAQ

Is MiniMax-M2 Instruct better than Sonar Pro Max?

On the index average, Sonar Pro Max leads MiniMax-M2 Instruct by 1.7 points (81.1 versus 79.4). The better choice depends on price, context and your task. MiniMax-M2 Instruct wins 4 benchmarks, Sonar Pro Max wins 8.

Which is cheaper, MiniMax-M2 Instruct or Sonar Pro Max?

MiniMax-M2 Instruct is cheaper on a blended 3:1 basis at about $10.09 per million tokens, versus $27.84 for Sonar Pro Max.

Which has the larger context window?

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

Are these models open weights?

MiniMax-M2 Instruct is open weights; Sonar Pro Max is proprietary.

Which should I choose for production?

If you need a single default, start with Sonar Pro Max for quality-sensitive work and MiniMax-M2 Instruct for high-volume, well-scoped tasks. Run both on a sample of your own traffic before locking in a choice.

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