Compare/MiniMax-M2.5 vs Llama 3.1 Nemotron Instruct 70B

MiniMax-M2.5vsLlama 3.1 Nemotron Instruct 70B

Side-by-side comparison of pricing, 12 benchmarks, and generation speed.

MiniMax

MiniMax-M2.5

Input
$0.3/M
Output
$1.2/M
Speed
47 tok/s
TTFT
1.40s
NVIDIA

Llama 3.1 Nemotron Instruct 70B

Input
$1.2/M
Output
$1.2/M
Speed
33 tok/s
TTFT
0.39s

Winner by Category

Cheaper
MiniMax-M2.5
Faster (tok/s)
MiniMax-M2.5
Lower Latency
Llama 3.1 Nemotron Instruct 70B
Benchmarks (7-5)
MiniMax-M2.5

Pricing Comparison

MetricMiniMax-M2.5Llama 3.1 Nemotron Instruct 70B
Input ($/M tokens)$0.3$1.2
Output ($/M tokens)$1.2$1.2
Cost for 1M input + 100K output tokens:
MiniMax-M2.5$0.42
Llama 3.1 Nemotron Instruct 70B$1.32

Speed Comparison

Output Speed (tokens/s) — higher is better
MiniMax-M2.5
47 tok/s
Llama 3.1 Nemotron Instruct 70B
33 tok/s
Time to First Token (seconds) — lower is better
MiniMax-M2.5
1.40s
Llama 3.1 Nemotron Instruct 70B
0.39s

Benchmark Comparison

Data from Artificial Analysis API — 12 benchmarks

Intelligence Index
41.913.4
Coding Index
37.410.8
Math Index
11.0
GPQA Diamond
84.8%46.5%
MMLU-Pro
69.0%
LiveCodeBench
16.9%
AIME 2025
11.0%
MATH-500
73.3%
Humanity's Last Exam
19.1%4.6%
SciCode
42.6%23.3%
IFBench
71.6%30.7%
TerminalBench
34.8%4.5%
MiniMax-M2.57 wins
5 winsLlama 3.1 Nemotron Instruct 70B

Frequently Asked Questions

Which is cheaper, MiniMax-M2.5 or Llama 3.1 Nemotron Instruct 70B?

MiniMax-M2.5 is cheaper overall. Its blended price (3:1 input/output ratio) is $0.53/M tokens vs $1.20/M for Llama 3.1 Nemotron Instruct 70B.

Which model performs better on benchmarks?

MiniMax-M2.5 wins 7 out of 12 benchmarks compared to 5 for Llama 3.1 Nemotron Instruct 70B. See the detailed benchmark chart above for per-category results.

Which is faster for real-time applications?

MiniMax-M2.5 generates tokens faster at 47 tok/s vs 33 tok/s. However, Llama 3.1 Nemotron Instruct 70B has lower time-to-first-token (0.39s vs 1.40s).

When should I use MiniMax-M2.5 vs Llama 3.1 Nemotron Instruct 70B?

Choose based on your priorities: MiniMax-M2.5 for lower cost, MiniMax-M2.5 for stronger benchmark performance, and MiniMax-M2.5 for faster generation. For latency-sensitive apps, check the TTFT comparison above.