Llama 3.3 70B Instruct vs MiniMax M2: Specs & Benchmark Comparison
| Characteristic | Llama 3.3 70B Instruct | MiniMax M2 |
|---|---|---|
| Company | Meta | MiniMax |
| Release Date | December 6, 2024 | October 26, 2025 |
| Parameters | 70B | 230B |
| Multimodal | No | No |
| Context (input) | 128K | 1.0M |
| Context (output) | 128K | 100K |
| Input Price / 1M | $0.88 | $1.00 |
| Output Price / 1M | $0.88 | $4.00 |
| Average Score | 0.8 | 0.8 |
| Benchmarks | ||
| GPQA | 0.5 | 0.8 |
| MMLU-Pro | 0.7 | 0.8 |
Visual Benchmark Comparison
Llama 3.3 70B Instruct
MiniMax M2
GPQA0.5 vs 0.8
0.5
0.8
MMLU-Pro0.7 vs 0.8
0.7
0.8
Verdict
MiniMax M2 leads in 2 out of 4 comparison categories.
Overall Performance
Both models show comparable average scores: Llama 3.3 70B Instruct — 0.8, MiniMax M2 — 0.8.
API Cost
Llama 3.3 70B Instruct is 2.8x cheaper: input $0.88/1M vs $1.00/1M tokens.
Context Window
MiniMax M2 supports a larger context: 1M vs 128K tokens.
Recency
MiniMax M2 is newer: released 10/26/2025 vs 12/6/2024.
More About These Models
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Frequently Asked Questions
Which is better for coding — Llama 3.3 70B Instruct or MiniMax M2?
Direct comparison on the SWE-Bench benchmark is not available. We recommend reviewing other metrics on the comparison page.
Which model is cheaper — Llama 3.3 70B Instruct or MiniMax M2?
Llama 3.3 70B Instruct is cheaper for input: $0.88 per 1M tokens vs $1.00.
Which has a larger context window — Llama 3.3 70B Instruct or MiniMax M2?
MiniMax M2 supports a larger context: 1,000,000 tokens vs 128,000.
The Llama 3.3 70B Instruct and MiniMax M2 comparison is updated for 2026. Data includes benchmark results, API pricing, context window size and other specifications. For more detailed information, visit the Llama 3.3 70B Instruct or MiniMax M2 page. See also the complete list of AI model comparisons.