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Llama 3.3 70B Instruct vs MiMo-V2.5

Detailed technical comparison between Llama 3.3 70B Instruct (Meta) and MiMo-V2.5 (Xiaomi). Review live API token pricing, context window capabilities, time-to-first-token latency, and verified benchmark scores side-by-side.

⚡ Executive Summary & Verdict

Comparison Snapshot

Llama 3.3 70B Instruct: 6 WinsvsMiMo-V2.5: 0 Wins
Context Leader

MiMo-V2.5

1,050,000 tokens
Agentic Tool-Calling

Tie

Equal Capability
Lowest Latency (TTFT)

Tie

Equal Speed
Input Price Leader

Llama 3.3 70B Instruct

$0.13 / MTok
Metaactive

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.

View Llama 3.3 70B Instruct Full Specs →
Xiaomiactive

MiMo-V2.5

MiMo-V2.5 is a native omnimodal model by Xiaomi. It delivers Pro-level agentic performance at roughly half the inference cost, while surpassing MiMo-V2-Omni in multimodal perception across image and video understanding...

View MiMo-V2.5 Full Specs →

Technical Specifications

🏆 = Superior Spec
SpecificationLlama 3.3 70B InstructMiMo-V2.5
ProviderMetaXiaomi
Context Window131,072 tokens1,050,000 tokens🏆
Agent Suitability83/100 (est.)Not yet benchmarked
Time to First Token (TTFT)280 ms (est.)No public TTFT data
Deployment Modelself hostablemanaged api
Production StabilityStable GA (est.)Beta Access (est.)
API AvailableYesYes
Released Date2024-12-062026-04-22

API Pricing Comparison

Input Price per Million Tokens

Llama 3.3 70B Instruct

$0.13

MiMo-V2.5

$0.14

Output Price per Million Tokens

Llama 3.3 70B Instruct

$0.40

MiMo-V2.5

$0.28

💡 Cost Ratio: Llama 3.3 70B Instruct is 1.1x cheaper per input token than MiMo-V2.5.

Want to test both models live?

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Benchmark Performance Metrics

Standardized Scores (0–100%)

Scores show verified raw accuracy percentages across standardized AI evaluation suites. Higher bars indicate superior performance in that domain.

MMLUGeneral knowledge & multi-task understanding
86.2%vs81.4%+4.8% Llama 3.3 70B Instruct
Llama 3.3 70B Instruct 🏆
MiMo-V2.5
HumanEvalPython coding & logic synthesis
88.0%vs79.6%+8.4% Llama 3.3 70B Instruct
Llama 3.3 70B Instruct 🏆
MiMo-V2.5
MATHComplex mathematical problem solving
75.0%vs53.4%+21.6% Llama 3.3 70B Instruct
Llama 3.3 70B Instruct 🏆
MiMo-V2.5
GPQAGraduate-level expert reasoning
52.0%vs38.8%+13.2% Llama 3.3 70B Instruct
Llama 3.3 70B Instruct 🏆
MiMo-V2.5
HellaSwagCommonsense reasoning and inference
88.5%vs81.0%+7.5% Llama 3.3 70B Instruct
Llama 3.3 70B Instruct 🏆
MiMo-V2.5
MT-BenchMulti-turn conversation flow quality
8.8%vs8.4%+0.4% Llama 3.3 70B Instruct
Llama 3.3 70B Instruct 🏆
MiMo-V2.5

Llama 3.3 70B Instruct Quirks & Gotchas

  • ▸Stable, well-documented self-hosted option with strong community support
  • ▸Outperformed by Llama 4 Maverick for agentic tool-calling workflows

MiMo-V2.5 Quirks & Gotchas

No developer gotchas reported.

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