Head-to-Head Model Comparison

Nemotron 3 Nano Omni 30B A3B Reasoning vs Mistral Small 4

Benchmarks, API Token Pricing, Context Window & Speed Comparison

GetInfoUs 연구팀 검토 완료최종 검토일: October 2026편집 정책

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Nemotron 3 Nano Omni 30B A3B ReasoningProfile

Mistral Small 4Profile

Multi-Model Arena Stack:

5-Model Matrix Workbench

Popular Matchups:

NVIDIA

Nemotron 3 Nano Omni 30B A3B Reasoning

네이티브 멀티모달 AI

NVIDIA의 Nemotron 3 Nano Omni 30B A3B Reasoning 모델은 텍스트와 이미지의 네이티브 멀티모달 이해 및 복합 문서·차트 분석에 최적화된 AI 모델로, 256K 컨텍스트 윈도우, 초당 105 토큰의 생성 속도, 종합 지능 지수 48/100점(1M 토큰당 입력 $0.2 / 출력 $0.6)을 제공합니다.

Intelligence Index48 / 100

Input Token:

$0.20 / 1M

Output Token:

$0.60 / 1M

Context Window:

256K tokens

SWE-bench Verified:

42%

Mistral AI

Mistral Small 4

초고속 저지연 추론 모델

Mistral AI의 Mistral Small 4 모델은 초저지연 실시간 대화, 고속 라우팅 및 대규모 트래픽 처리에 최적화된 AI 모델로, 256K 컨텍스트 윈도우, 초당 120 토큰의 생성 속도, 종합 지능 지수 48/100점(1M 토큰당 입력 $0.1 / 출력 $0.3)을 제공합니다.

Intelligence Index48 / 100

Input Token:

$0.10 / 1M

Output Token:

$0.30 / 1M

Context Window:

256K tokens

SWE-bench Verified:

44.5%

한눈에 보는 핵심 차이점

Mistral Small 4 is 2.0x cheaper for API usage (input + output tokens combined).
Mistral Small 4 is faster at 120 tok/s vs 105 tok/s.
Mistral Small 4 leads on SWE-bench coding (44.5% vs 42.0%).

Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →

Feature	Nemotron 3 Nano Omni 30B A3B Reasoning	Mistral Small 4
Intelligence Index Composite reasoning & knowledge score (0-100)	48	48
Provider	NVIDIA	Mistral AI
Input Price Cost per million input tokens	$0.20 / 1M	$0.10 / 1M
Output Price Cost per million output tokens	$0.60 / 1M	$0.30 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$0.14 / 1M	$0.07 / 1M
Context Window Maximum input + output tokens	256K tokens~384 A4 pages of text	256K tokens~384 A4 pages of text
Max Output Tokens Per single request	16K	16K
Throughput Speed Tokens generated per second	105 tok/s	120 tok/s
SWE-bench Verified Real-world software engineering	42%	44.5%
GPQA Diamond Graduate-level reasoning	56.5%	56%
Cached Input Price Prompt caching discount per 1M tokens	$0.05 / 1M	$0.03 / 1M

부문별 우위 모델

At-a-glance decision framework

Coding

Mistral Small 4

+2.5% SWE-bench lead

Cost

Mistral Small 4

2.0x cheaper monthly runtime

Speed

Mistral Small 4

+14% faster generation

Context

Tied

256K tokens window

검증된 벤치마크 점수 비교

Official evaluation metrics verified by independent third-party research labs.

Nemotron 3 Nano Omni 30B A3B ReasoningMistral Small 4

SWE-bench Verified (Autonomous Coding)

Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.

42%vs44.5%

GPQA Diamond (Doctorate-Level Science & Math)

Challenging questions created by domain experts to test complex PhD-level reasoning.

56.5%vs56%

MMLU-Pro (Multi-task Language Understanding)

Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.

77.2%vs78%

LMSYS Chatbot Arena Elo

Crowdsourced human preference evaluation based on blind, head-to-head model battles.

1310ptsvs1315pts

Terminal-Bench (Agentic Coding & Terminal Use)

Autonomous multi-step tasks executed inside a real command-line terminal environment.

36.5%vs38%

AIME (Advanced Math Competition)

American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.

66%vs66%

Long-Context Reasoning

Accuracy when reasoning over very large inputs that fill the model context window.

78%vs80%

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

105 tok/s vs120 tok/s

지연 시간(Latency) 및 응답 속도

Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.

Time to First Token (TTFT)Lower is better

Nemotron 3 Nano Omni 30B A3B Reasoning0.38s

Mistral Small 40.34s

Est. End-to-End Response (500 tokens)TTFT + generation time

Nemotron 3 Nano Omni 30B A3B Reasoning5.14s

Mistral Small 44.51s

실시간 API 토큰 비용 시뮬레이터

Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.

Daily Input Tokens100K / day

10K500K1M

Daily Output Tokens30K / day

5K150K300K

Prompt Cache Hit Ratio50% cached

0% (Cold)50%90% (Warm)

Nemotron 3 Nano Omni 30B A3B Reasoning Monthly API Bill

$0.92 / month

$0.2/1M in · $0.6/1M out

Mistral Small 4 Monthly API Bill

$0.47 / month

$0.1/1M in · $0.3/1M out

Mistral Small 4 saves approximately $0.45 / month (49%) under this workload.2.0x Savings

Nemotron 3 Nano Omni 30B A3B Reasoning · Strengths & Key Advantages

256K 컨텍스트 윈도우 및 최대 16K 출력 토큰 생성 지원 (SWE-bench Verified 42% · GPQA Diamond 56.5%)
초당 105 토큰의 빠른 처리 속도와 380ms에 불과한 첫 토큰 지연 시간(TTFT)
오픈 웨이트 아키텍처 (30B (3B MoE))를 통해 vLLM, SGLang, Ollama 기반 자체 GPU 서버 구축 및 파인튜닝 가능

Considerations & Trade-offs

비양자화 전체 정밀도로 로컬 서버에서 구동하려면 충분한 GPU VRAM 용량이 필요합니다
초고난도 학술 연구 및 수학 증명 과제에서는 상위 대형 추론 특화 모델이 더 깊은 분석을 제공할 수 있습니다

Mistral Small 4 · Strengths & Key Advantages

256K 컨텍스트 윈도우 및 최대 16K 출력 토큰 생성 지원 (SWE-bench Verified 44.5% · GPQA Diamond 56%)
초당 120 토큰의 빠른 처리 속도와 340ms에 불과한 첫 토큰 지연 시간(TTFT)
오픈 웨이트 아키텍처 (24B)를 통해 vLLM, SGLang, Ollama 기반 자체 GPU 서버 구축 및 파인튜닝 가능

Considerations & Trade-offs

비양자화 전체 정밀도로 로컬 서버에서 구동하려면 충분한 GPU VRAM 용량이 필요합니다
초고난도 학술 연구 및 수학 증명 과제에서는 상위 대형 추론 특화 모델이 더 깊은 분석을 제공할 수 있습니다

Token Use & Task Economics

Estimated cost and token consumption to complete one representative agentic task.

Metric	Nemotron 3 Nano Omni 30B A3B Reasoning	Mistral Small 4
Cost per Task Estimated USD to finish one task	$0.22	$0.12
Output Tokens / Task Tokens generated per task	28K	28K
Reasoning Tokens / Task Thinking tokens burned per task	12K	12K

기술 사양 (Specifications)

Architecture, release timeline, capabilities, and modalities.

Feature	Nemotron 3 Nano Omni 30B A3B Reasoning	Mistral Small 4
Official API Model ID (SDK)	nemotron-3-nano-omni-30b-a3b	mistral-small-4-latest
API Protocol	OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI	OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
Release Date	2026-04	2026-03
Knowledge Cutoff	February 2026	January 2026
Architecture	Omnimodal Sparse MoE (30B Total / 3B Active)	Next-Gen Compact Multimodal Transformer
Parameters	30B (3B active MoE)	24B
Enterprise Rate Limits (RPM / TPM)	Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud	Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud
Long-Context Tier (>128K/200K)	Flat rate ($0.2/1M in) across full 256K window	Flat rate ($0.1/1M in) across full 256K window
Prompt Cache Policy & TTL	Cached input at $0.05/1M tokens	Cached input at $0.03/1M tokens
Computer Use / GUI Agent	API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)	API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)
MCP & Parallel Tool Calling	Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema	Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
Web Search Grounding & Sandbox	Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools	Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools
Official Fine-Tuning Support	Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)	Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)
Multimodal Token Billing	Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec)	Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)
Quantization & Min GPU VRAM	BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 19 GB VRAM (4-bit Quantized) · 65 GB VRAM (Native BF16)	BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 15 GB VRAM (4-bit Quantized) · 52 GB VRAM (Native BF16)
Safety & Frontier Classification	Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma)	Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma)
Enterprise Compliance (ZDR/HIPAA/SOC2)	100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control	100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control
Input Modalities	text, vision, audio	text, vision
Output Modalities	text	text

Nemotron 3 Nano Omni 30B A3B Reasoning vs Mistral Small 4: 핵심 요약 문답 (FAQ)

Which model is faster?

Mistral Small 4 is faster, generating 120 tokens per second compared with 105 tokens per second.

Which model is cheaper to run?

Mistral Small 4 is cheaper at $0.07 per 1M tokens blended, compared with $0.14 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Mistral Small 4 has lower latency, with a time to first token of 0.34s compared with 0.38s.

종합 평가

Nemotron 3 Nano Omni 30B A3B Reasoning(텍스트와 이미지의 네이티브 멀티모달 이해 및 복합 문서·차트 분석, 엔터프라이즈 RAG 지식베이스 및 대규모 프로덕션 API 연동에 최적.)와 Mistral Small 4(초저지연 실시간 대화, 고속 라우팅 및 대규모 트래픽 처리, 엔터프라이즈 RAG 지식베이스 및 대규모 프로덕션 API 연동에 최적.) 모두 뛰어난 성능을 자랑합니다. 고난도 추론과 코딩 벤치마크에서는 Nemotron 3 Nano Omni 30B A3B Reasoning가 앞서며, 토큰 생성 속도에서는 Mistral Small 4가 빠르고, 대규모 API 운영 비용 면에서는 Mistral Small 4가 더 경제적입니다.

자주 묻는 질문 (FAQ)

코딩과 복잡한 추론에는 Nemotron 3 Nano Omni 30B A3B Reasoning와 Mistral Small 4 중 어느 모델이 더 나은가요?+

종합 지능 지수 및 코딩 벤치마크에서는 Nemotron 3 Nano Omni 30B A3B Reasoning가 우위를 보입니다. 상단의 SWE-bench 및 GPQA 점수를 함께 확인해 보세요.

Nemotron 3 Nano Omni 30B A3B Reasoning와 Mistral Small 4의 API 요금 차이는 얼마인가요?+

Nemotron 3 Nano Omni 30B A3B Reasoning는 100만 토큰당 입력 $0.20 / 출력 $0.60이며, Mistral Small 4는 입력 $0.10 / 출력 $0.30입니다. 혼합 비용 기준으로는 Mistral Small 4가 더 저렴합니다.

어느 모델이 더 큰 컨텍스트 윈도우와 빠른 속도를 제공하나요?+

컨텍스트 길이는 Nemotron 3 Nano Omni 30B A3B Reasoning가 256K 토큰, Mistral Small 4가 256K 토큰를 지원하며, 출력 속도 면에서는 Mistral Small 4가 더 빠릅니다.

AI Terminology & Guide

Explore Glossary →

Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.

Tokens & Pricing Context Window AI Benchmarks Reasoning Models Tool Calling Model Context Protocol (MCP)

Nemotron 3 Nano Omni 30B A3B Reasoning vs Mistral Small 4

원하는 AI 모델 선택 및 실시간 비교

Nemotron 3 Nano Omni 30B A3B Reasoning

Mistral Small 4

부문별 우위 모델

검증된 벤치마크 점수 비교

지연 시간(Latency) 및 응답 속도

실시간 API 토큰 비용 시뮬레이터

Nemotron 3 Nano Omni 30B A3B Reasoning · Strengths & Key Advantages

Considerations & Trade-offs

Mistral Small 4 · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

기술 사양 (Specifications)

Nemotron 3 Nano Omni 30B A3B Reasoning vs Mistral Small 4: 핵심 요약 문답 (FAQ)

종합 평가

자주 묻는 질문 (FAQ)

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