Head-to-Head Model Comparison

Gemini 3.8 Flash vs Llama 5

Benchmarks, API Token Pricing, Context Window & Speed Comparison

GetInfoUs 연구팀 검토 완료최종 검토일: October 2026편집 정책

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Gemini 3.8 FlashProfile

Llama 5Profile

Multi-Model Arena Stack:

5-Model Matrix Workbench

Popular Matchups:

Google

Gemini 3.8 Flash

초고속 저지연 추론 모델

Google의 Gemini 3.8 Flash 모델은 초저지연 실시간 대화, 고속 라우팅 및 대규모 트래픽 처리에 최적화된 AI 모델로, 1.0M 컨텍스트 윈도우, 초당 175 토큰의 생성 속도, 종합 지능 지수 87/100점(1M 토큰당 입력 $0.75 / 출력 $3.75)을 제공합니다.

Intelligence Index87 / 100

Input Token:

$0.75 / 1M

Output Token:

$3.75 / 1M

Context Window:

1.05M tokens

SWE-bench Verified:

74.8%

Llama 5

오픈 웨이트 파운데이션 모델

Meta의 Llama 5 모델은 프라이빗 클라우드 자체 호스팅, 파인튜닝 및 완벽한 데이터 주권 확보에 최적화된 AI 모델로, 5M 컨텍스트 윈도우, 초당 65 토큰의 생성 속도, 종합 지능 지수 94/100점(무료 오픈 웨이트 제공)을 제공합니다.

Intelligence Index94 / 100

Input Token:

$0.00 / 1M

Output Token:

$0.00 / 1M

Context Window:

5M tokens

SWE-bench Verified:

74%

한눈에 보는 핵심 차이점

Llama 5 is 1.0x cheaper for API usage (input + output tokens combined).
Llama 5 has a larger context window (5M vs 1M tokens).
Gemini 3.8 Flash is faster at 175 tok/s vs 65 tok/s.
Gemini 3.8 Flash leads on SWE-bench coding (74.8% vs 74.0%).

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

Feature	Gemini 3.8 Flash	Llama 5
Intelligence Index Composite reasoning & knowledge score (0-100)	87	94
Provider	Google	Meta
Input Price Cost per million input tokens	$0.75 / 1M	$0.00 / 1M
Output Price Cost per million output tokens	$3.75 / 1M	$0.00 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$0.66 / 1M	$0.00 / 1M
Context Window Maximum input + output tokens	1.05M tokens~1,573 A4 pages of text	5M tokens~7,500 A4 pages of text
Max Output Tokens Per single request	66K	128K
Throughput Speed Tokens generated per second	175 tok/s	65 tok/s
SWE-bench Verified Real-world software engineering	74.8%	74%
GPQA Diamond Graduate-level reasoning	84%	84%
Cached Input Price Prompt caching discount per 1M tokens	$0.19 / 1M	$0.00 / 1M

부문별 우위 모델

At-a-glance decision framework

Coding

Gemini 3.8 Flash

+0.8% SWE-bench lead

Cost

Llama 5

1.0x cheaper monthly runtime

Speed

Gemini 3.8 Flash

+169% faster generation

Context

Llama 5

5M tokens window

검증된 벤치마크 점수 비교

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

Gemini 3.8 FlashLlama 5

SWE-bench Verified (Autonomous Coding)

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

74.8%vs74%

GPQA Diamond (Doctorate-Level Science & Math)

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

84%vs84%

MMLU-Pro (Multi-task Language Understanding)

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

88.8%vs87%

LMSYS Chatbot Arena Elo

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

1480ptsvs1485pts

LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

N/Avs68%

AIME (Advanced Math Competition)

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

89.5%vs88%

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

175 tok/s vs65 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

Gemini 3.8 Flash0.39s

Llama 50.85s

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

Gemini 3.8 Flash3.25s

Llama 58.54s

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)

Gemini 3.8 Flash Monthly API Bill

$4.78 / month

$0.75/1M in · $3.75/1M out

Llama 5 Monthly API Bill

$0.00 / month

$0/1M in · $0/1M out

Llama 5 saves approximately $4.78 / month (100%) under this workload.1.0x Savings

Gemini 3.8 Flash · Strengths & Key Advantages

1.0M 컨텍스트 윈도우 및 최대 66K 출력 토큰 생성 지원 (SWE-bench Verified 74.8% · GPQA Diamond 84%)
초당 175 토큰의 빠른 처리 속도와 390ms에 불과한 첫 토큰 지연 시간(TTFT)
합리적인 API 요금 체계(1M 토큰당 입력 $0.75 / 출력 $3.75)와 프롬프트 캐싱, 함수 호출 및 정형화된 JSON 출력 완벽 지원

Considerations & Trade-offs

독점 클라우드 전용 모델로 로컬 오프라인 서버에 가중치를 다운로드하여 실행할 수 없습니다
초고난도 학술 연구 및 수학 증명 과제에서는 상위 대형 추론 특화 모델이 더 깊은 분석을 제공할 수 있습니다

Llama 5 · Strengths & Key Advantages

5M 컨텍스트 윈도우 및 최대 128K 출력 토큰 생성 지원 (SWE-bench Verified 74% · GPQA Diamond 84%)
초당 65 토큰의 빠른 처리 속도와 850ms에 불과한 첫 토큰 지연 시간(TTFT)
오픈 웨이트 아키텍처 (600B+ total (~40-80B ))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	Gemini 3.8 Flash	Llama 5
Cost per Task Estimated USD to finish one task	$1.20	$0.00
Output Tokens / Task Tokens generated per task	44K	40K
Reasoning Tokens / Task Thinking tokens burned per task	21K	20K

기술 사양 (Specifications)

Architecture, release timeline, capabilities, and modalities.

Feature	Gemini 3.8 Flash	Llama 5
Official API Model ID (SDK)	models/gemini-3-8-flash	meta-llama/Llama-5
API Protocol	Google Gemini API (generateContent) + OpenAI-Compatible SDK	OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
Release Date	2026-09	2026-04
Knowledge Cutoff	June 2026	January 2026
Architecture	Late-2026 optimized sparse multimodal transformer	Mixture-of-Experts with recursive self-improvement (~600B total, 40-80B active)
Parameters	Confidential	600B+ total (~40-80B active)
Enterprise Rate Limits (RPM / TPM)	10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM	Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud
Long-Context Tier (>128K/200K)	Standard rate up to 200K tokens; 2x input/output tier above 200K tokens	Free across full context window (only KV-cache VRAM scales)
Prompt Cache Policy & TTL	Implicit + Explicit Context Caching at $0.1875/1M with configurable TTL	Automatic prefix KV-caching in vLLM / SGLang (0 cost)
Computer Use / GUI Agent	Supported (Screen coordinate grounding, browser & desktop GUI action loops)	Supported (Screen coordinate grounding, browser & desktop GUI action loops)
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	Built-in Google Search Grounding + Managed Python Code Execution Sandbox	Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools
Official Fine-Tuning Support	Vertex AI Supervised Adapter Tuning & Context Distillation	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) · Video (~258–300 tokens/sec)	Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec) · Video (~258–300 tokens/sec)
Quantization & Min GPU VRAM	Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API)	BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 372 GB VRAM (4-bit Quantized) · 1290 GB VRAM (Native BF16)
Safety & Frontier Classification	Google DeepMind Frontier Safety Framework Verified	Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma)
Enterprise Compliance (ZDR/HIPAA/SOC2)	SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier	100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control
Input Modalities	text, vision, audio, video	text, vision, video, audio
Output Modalities	text	text

Gemini 3.8 Flash vs Llama 5: 핵심 요약 문답 (FAQ)

Which is more intelligent, Gemini 3.8 Flash or Llama 5?

Llama 5 is more intelligent. It scores 94 compared with 87 on the composite Intelligence Index.

Which model is faster?

Gemini 3.8 Flash is faster, generating 175 tokens per second compared with 65 tokens per second.

Which model is cheaper to run?

Llama 5 is cheaper at $0.00 per 1M tokens blended, compared with $0.66 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Gemini 3.8 Flash has lower latency, with a time to first token of 0.39s compared with 0.85s.

Which model has a larger context window?

Llama 5 has a larger context window, supporting 5M tokens compared with 1.05M tokens.

종합 평가

Gemini 3.8 Flash(초저지연 실시간 대화, 고속 라우팅 및 대규모 트래픽 처리, 엔터프라이즈 RAG 지식베이스 및 대규모 프로덕션 API 연동에 최적.)와 Llama 5(프라이빗 클라우드 자체 호스팅, 파인튜닝 및 완벽한 데이터 주권 확보, 엔터프라이즈 RAG 지식베이스 및 대규모 프로덕션 API 연동에 최적.) 모두 뛰어난 성능을 자랑합니다. 고난도 추론과 코딩 벤치마크에서는 Llama 5가 앞서며, 토큰 생성 속도에서는 Gemini 3.8 Flash가 빠르고, 대규모 API 운영 비용 면에서는 Llama 5가 더 경제적입니다.

자주 묻는 질문 (FAQ)

코딩과 복잡한 추론에는 Gemini 3.8 Flash와 Llama 5 중 어느 모델이 더 나은가요?+

종합 지능 지수 및 코딩 벤치마크에서는 Llama 5가 우위를 보입니다. 상단의 SWE-bench 및 GPQA 점수를 함께 확인해 보세요.

Gemini 3.8 Flash와 Llama 5의 API 요금 차이는 얼마인가요?+

Gemini 3.8 Flash는 100만 토큰당 입력 $0.75 / 출력 $3.75이며, Llama 5는 입력 $0.00 / 출력 $0.00입니다. 혼합 비용 기준으로는 Llama 5가 더 저렴합니다.

어느 모델이 더 큰 컨텍스트 윈도우와 빠른 속도를 제공하나요?+

컨텍스트 길이는 Gemini 3.8 Flash가 1.05M 토큰, Llama 5가 5M 토큰를 지원하며, 출력 속도 면에서는 Gemini 3.8 Flash가 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)

Gemini 3.8 Flash vs Llama 5

원하는 AI 모델 선택 및 실시간 비교

Gemini 3.8 Flash

Llama 5

부문별 우위 모델

검증된 벤치마크 점수 비교

지연 시간(Latency) 및 응답 속도

실시간 API 토큰 비용 시뮬레이터

Gemini 3.8 Flash · Strengths & Key Advantages

Considerations & Trade-offs

Llama 5 · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

기술 사양 (Specifications)

Gemini 3.8 Flash vs Llama 5: 핵심 요약 문답 (FAQ)

종합 평가

자주 묻는 질문 (FAQ)

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