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Llama 3.3 70B Instruct vs MiniMax M2.5

How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for Llama 3.3 70B Instruct and MiniMax M2.5.

Meta

Llama 3.3 70B Instruct

Meta's state-of-the-art open weights model, providing enterprise-grade reasoning and logic. Exceptionally powerful for self-hosted customer support, text generation, and tooling workflows.

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MiniMax

MiniMax M2.5

MiniMax-M2.5 is a SOTA large language model designed for real-world productivity. Trained in a diverse range of complex real-world digital working environments, M2.5 builds upon the coding expertise of M2.1...

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Technical Specifications

SpecificationLlama 3.3 70B InstructMiniMax M2.5
ProviderMetaMiniMax
Context Window131,072 tokens204,800 tokens
Agent Suitability83/100N/A
Time to First Token (TTFT)280 msN/A
Deployment Modelself hostablemanaged api
Production Stabilitystablestable
API AvailableYesYes
Released Date2024-12-062026-02-12

API Pricing Comparison

Input Price per Million Tokens

Llama 3.3 70B Instruct

$0.10

MiniMax M2.5

$0.12

Output Price per Million Tokens

Llama 3.3 70B Instruct

$0.32

MiniMax M2.5

$0.48

Want to test both models live?

Run side-by-side prompt prompts in our dynamic Sandbox. Check execution speeds, latency metrics, and compute actual costs in real-time.

Benchmark Performance Metrics

Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.

MMLUGeneral knowledge & multi-task understanding
8620.0%vsN/A
Llama 3.3 70B Instruct
MiniMax M2.5
HumanEvalPython coding & logic synthesis
8800.0%vsN/A
Llama 3.3 70B Instruct
MiniMax M2.5
MATHComplex mathematical problem solving
7500.0%vsN/A
Llama 3.3 70B Instruct
MiniMax M2.5
GPQAGraduate-level expert reasoning
5200.0%vsN/A
Llama 3.3 70B Instruct
MiniMax M2.5
HellaSwagCommonsense reasoning and inference
8850.0%vsN/A
Llama 3.3 70B Instruct
MiniMax M2.5
MT-BenchMulti-turn conversation flow quality
880.0%vsN/A
Llama 3.3 70B Instruct
MiniMax M2.5

Llama 3.3 70B Instruct Quirks & Gotchas

  • โ–ธStable, well-documented self-hosted option with strong community support
  • โ–ธOutperformed by Llama 4 Maverick for agentic tool-calling workflows

MiniMax M2.5 Quirks & Gotchas

No developer gotchas reported.