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MiniMax: MiniMax M2.5 vs Anthropic: Claude Sonnet 4.6: Coding Performance with 10 Evaluators

We analyze the coding capabilities of MiniMax: MiniMax M2.5 and Anthropic: Claude Sonnet 4.6 through rigorous testing by 10 independent evaluators.

MiniMax: MiniMax M2.5

3.4

preference score

vs

Anthropic: Claude Sonnet 4.6

6.6

preference score

Judges ranked the responses in this Run against each other; the rank is mapped onto a 0–10 scale. It shows which response was preferred, not how good either one is — and it is not a percentage, a pass rate, or a check that the output was correct.

Sample size for this comparison was not recorded. Treat it as directional.

Evidence clarification: this article predates recorded sample provenance. Treat its conclusions as claims about the displayed examples; they do not establish general model superiority, verified correctness, or production suitability.

Key Findings

Top PerformanceAnthropic: Claude Sonnet 4.6

Secured the #1 rank with an overall score of 6.58 in coding tasks.

Cost AdvantageMiniMax: MiniMax M2.5

Offers significantly lower costs per token for high-volume coding workflows.

Instruction FollowingAnthropic: Claude Sonnet 4.6

Demonstrated superior ability to interpret and execute complex coding prompts.

Specifications

SpecMiniMax: MiniMax M2.5Anthropic: Claude Sonnet 4.6
Providerminimaxanthropic
Context Length205K1.0M
Input Price (per 1M tokens)$0.27$3.00
Output Price (per 1M tokens)$1.08$15.00
Max Output Tokens128,000128,000
Tierstandardfrontier

Our Verdict

Anthropic: Claude Sonnet 4.6 stands out as the clear winner for coding tasks, offering superior accuracy and instruction adherence. While MiniMax: MiniMax M2.5 is more budget-friendly, the performance gap makes Claude the preferred choice for mission-critical development.

Overview

In this comparative analysis, we evaluate the coding performance of two powerful LLMs: MiniMax: MiniMax M2.5 and Anthropic: Claude Sonnet 4.6. Our evaluation suite, conducted by 10 expert evaluators, focuses specifically on real-world coding tasks, measuring accuracy and instruction-following capabilities. The results highlight distinct trade-offs between performance precision and operational cost.

Benchmark Results

The comparative evaluation reveals a clear hierarchy in coding proficiency. Anthropic: Claude Sonnet 4.6 secures the top position, demonstrating superior reliability in code generation and logic adherence compared to the MiniMax M2.5 model.

ModelRankOverall ScoreAccuracyInstruction Following
Anthropic: Claude Sonnet 4.616.586.586.58
MiniMax: MiniMax M2.523.423.423.42

Criteria Breakdown

The evaluation centered on two primary pillars: Accuracy and Instruction Following. In coding contexts, these criteria are non-negotiable. Anthropic: Claude Sonnet 4.6 outperformed its counterpart by a significant margin of 3.16 points, indicating that it is better equipped to handle complex syntax, edge cases, and specific developer constraints.

Cost & Latency

Efficiency is a critical component for production-grade software development. While MiniMax: MiniMax M2.5 offers a much lower cost profile, the performance gap reflected in the scores suggests that Claude Sonnet 4.6 provides higher value for tasks requiring extreme precision.

  • MiniMax: MiniMax M2.5: $0.002185 total cost for the test set, with a cost per output token of $0.001281.
  • Anthropic: Claude Sonnet 4.6: $0.014196 total cost for the test set, with a cost per output token of $0.018778.

Use Cases

Anthropic: Claude Sonnet 4.6 is best suited for complex architectural design, debugging legacy codebases, and high-stakes production software where accuracy is the highest priority. MiniMax: MiniMax M2.5 serves as an economical alternative for high-volume, repetitive coding tasks, documentation generation, or simple script drafting where cost-efficiency is prioritized over absolute precision.

Verdict

Based on our comparative evaluation focusing on Coding Performance with 10 Evaluators, Anthropic: Claude Sonnet 4.6 is the superior choice for developers demanding high-fidelity code generation. While MiniMax: MiniMax M2.5 provides a cost-effective alternative, the performance spread confirms that Claude remains the benchmark leader in this specific coding suite.

Backed by real data

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See every response, score, and evaluator judgment behind this comparison. All data from PeerLM's blind evaluation pipeline.

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Methodology

Evaluated using PeerLM's blind evaluation pipeline with 4 responses per model across 2 criteria.