Back to Value Frontier

NVIDIA: Llama 3.1 Nemotron Ultra 253B v1 vs Xiaomi: MiMo-V2-Omni

Head-to-head API cost, context, and performance comparison. Synced at 3:28:30 AM.

Executive Summary

When evaluating NVIDIA: Llama 3.1 Nemotron Ultra 253B v1 against Xiaomi: MiMo-V2-Omni, the pricing structure is a key differentiator. Both models are remarkably similar in API costs.

However, when looking at raw reasoning capabilities, Xiaomi: MiMo-V2-Omni leads with a statistical ELO score of 1191. For tasks involving complex logic, coding, or instruction-following, developers might prefer Xiaomi: MiMo-V2-Omni, provided their budget allows for the API burn rate.

Raw Technical comparison

Metric
NVIDIA: Llama 3.1 Nemotron Ultra 253B v1
Xiaomi: MiMo-V2-Omni
Performance (ELO)
1191
1191
Input Cost / 1M
$0.60
$0.40
Output Cost / 1M
$1.80
$2.00
Context Window
131,072 tokens
262,144 tokens

Verdict

If you are looking for pure performance and capability, Tie is statistically superior. However, if API burn rate is the primary concern, Tie wins out aggressively in pricing.

People Also Ask

Is NVIDIA: Llama 3.1 Nemotron Ultra 253B v1 cheaper than Xiaomi: MiMo-V2-Omni?

No. Xiaomi: MiMo-V2-Omni is the more cost-effective model, operating at a lower price point per 1 million tokens.

Which model has the larger context window?

The Xiaomi: MiMo-V2-Omni model has the advantage in memory, offering a massive 262,144 token limit for document ingestion.

Related Comparisons

Compare NVIDIA: Llama 3.1 Nemotron Ultra 253B v1 vs MiniMax: MiniMax M2.5 (free)Compare NVIDIA: Llama 3.1 Nemotron Ultra 253B v1 vs StepFun: Step 3.5 Flash (free)Compare NVIDIA: Llama 3.1 Nemotron Ultra 253B v1 vs NVIDIA: Nemotron 3 Nano 30B A3B (free)Compare NVIDIA: Llama 3.1 Nemotron Ultra 253B v1 vs Arcee AI: Trinity Mini (free)