Head-to-head · frontier vs frontier

Claude Sonnet 4.5 Max vs o4 Reasoning: which model should you choose?

We compared Claude Sonnet 4.5 Max and o4 Reasoning on price, context window and 12 benchmarks. o4 Reasoning has the stronger average benchmark score; Claude Sonnet 4.5 Max is cheaper on a blended 3:1 basis.

Anthropic

Claude Sonnet 4.5 Max

Claude Sonnet 4.5 Max is a frontier model from Anthropic. It offers a 1,000,000-token context window, costs $19.90 per million input tokens and $95.47 per million output tokens, and averages 87.2 across the index's benchmark suite.

Input
$19.90 / 1M
Output
$95.47 / 1M
Context
1,000,000
Avg score
87.2
Open weights
No
Full Claude Sonnet 4.5 Max page
OpenAI

o4 Reasoning

o4 Reasoning is a frontier model from OpenAI. It offers a 1,000,000-token context window, costs $19.69 per million input tokens and $103.53 per million output tokens, and averages 87.5 across the index's benchmark suite.

Input
$19.69 / 1M
Output
$103.53 / 1M
Context
1,000,000
Avg score
87.5
Open weights
No
Full o4 Reasoning page

Specification comparison

SpecClaude Sonnet 4.5 Maxo4 ReasoningEdge
Input price / 1M$19.90$19.69B
Output price / 1M$95.47$103.53A
Context window1,000,0001,000,000Tie
Max output65,536128,000B
Average score87.287.5B
Arena Elo1474.91472.2A
Open weightsNoNoTie

Benchmark comparison

Claude Sonnet 4.5 Max wins 6, o4 Reasoning wins 5, and 1 benchmarks are tied. The table shows the modelled score for each model and the gap.

BenchmarkClaude Sonnet 4.5 Maxo4 ReasoningGapWinner
MMLU-Pro86.186.10.0Tie
GPQA Diamond84.484.00.4Claude Sonnet 4.5 Max
SWE-bench Verified80.276.43.8Claude Sonnet 4.5 Max
HumanEval92.490.22.2Claude Sonnet 4.5 Max
MATH-50092.894.82.0o4 Reasoning
AIME 202585.490.34.9o4 Reasoning
LiveCodeBench82.883.40.6o4 Reasoning
IFEval92.994.51.6o4 Reasoning
TruthfulQA87.389.01.7o4 Reasoning
HellaSwag93.192.40.7Claude Sonnet 4.5 Max
MMMU82.081.80.2Claude Sonnet 4.5 Max
Arena Elo1474.91472.22.7Claude Sonnet 4.5 Max

Price analysis

On a blended 3:1 input-to-output basis, Claude Sonnet 4.5 Max costs about $38.79 per million tokens and o4 Reasoning costs about $40.65. Claude Sonnet 4.5 Max is roughly 5% cheaper than o4 Reasoning. At high volume, that gap compounds quickly, so price should carry real weight unless the quality difference is decisive.

Both models list a 1,000,000-token context window. That is enough for long documents, large codebases and multi-step agent traces.

Verdict

Across 12 shared benchmarks, Claude Sonnet 4.5 Max wins 6, o4 Reasoning wins 5, and 1 are tied. On the index average, o4 Reasoning leads Claude Sonnet 4.5 Max by 0.3 points (87.5 versus 87.2).

The price picture favours Claude Sonnet 4.5 Max. 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 o4 Reasoning for quality-sensitive work and Claude Sonnet 4.5 Max for high-volume, well-scoped tasks. Run both on a sample of your own traffic before locking in a choice.

Choose Claude Sonnet 4.5 Max if

  • Unit cost matters and you want the cheaper blended price.

Choose o4 Reasoning if

  • You want the higher average benchmark score in this index.
  • You need the larger 128,000-token output limit.

FAQ

Is Claude Sonnet 4.5 Max better than o4 Reasoning?

On the index average, o4 Reasoning leads Claude Sonnet 4.5 Max by 0.3 points (87.5 versus 87.2). The better choice depends on price, context and your task. Claude Sonnet 4.5 Max wins 6 benchmarks, o4 Reasoning wins 5.

Which is cheaper, Claude Sonnet 4.5 Max or o4 Reasoning?

Claude Sonnet 4.5 Max is cheaper on a blended 3:1 basis at about $38.79 per million tokens, versus $40.65 for o4 Reasoning.

Which has the larger context window?

Both models list a 1,000,000-token context window.

Are these models open weights?

Claude Sonnet 4.5 Max is proprietary; o4 Reasoning is proprietary.

Which should I choose for production?

If you need a single default, start with o4 Reasoning for quality-sensitive work and Claude Sonnet 4.5 Max for high-volume, well-scoped tasks. Run both on a sample of your own traffic before locking in a choice.

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