Head-to-Head Model Comparison

GPT-2 vs LLaMA-1 (65B)

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Ditinjau oleh tim riset GetInfoUsPeninjauan terakhir: October 2026Kebijakan editorial

Ganti & Bandingkan Model Apa Saja

Select any AI models from our verified benchmark database to generate live side-by-side matrices.

GPT-2Profile

LLaMA-1 (65B)Profile

Multi-Model Arena Stack:

5-Model Matrix Workbench

Popular Matchups:

OpenAI

GPT-2

Model Dasar Bobot Terbuka

GPT-2 dari OpenAI adalah model AI yang dirancang untuk self-hosting di server pribadi, fine-tuning, dan kedaulatan data penuh, menghadirkan jendela konteks 1K, kecepatan 120 token/detik, indeks kecerdasan 12/100, serta akses gratis open-wei

Intelligence Index12 / 100

Input Token:

$0.00 / 1M

Output Token:

$0.00 / 1M

Context Window:

1K tokens

SWE-bench Verified:

N/A

LLaMA-1 (65B)

Model Dasar Bobot Terbuka

LLaMA-1 (65B) dari Meta adalah model AI yang dirancang untuk self-hosting di server pribadi, fine-tuning, dan kedaulatan data penuh, menghadirkan jendela konteks 2K, kecepatan 45 token/detik, indeks kecerdasan 25/100, serta akses gratis ope

Intelligence Index25 / 100

Input Token:

$0.00 / 1M

Output Token:

$0.00 / 1M

Context Window:

2K tokens

SWE-bench Verified:

N/A

Perbedaan Utama Sekilas

Both models cost the same under this workload — choose on capability, not price.
LLaMA-1 (65B) has a larger context window (2K vs 1K tokens).
GPT-2 is faster at 120 tok/s vs 45 tok/s.

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

Feature	GPT-2	LLaMA-1 (65B)
Intelligence Index Composite reasoning & knowledge score (0-100)	12	25
Provider	OpenAI	Meta
Input Price Cost per million input tokens	$0.00 / 1M	$0.00 / 1M
Output Price Cost per million output tokens	$0.00 / 1M	$0.00 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$0.00 / 1M	$0.00 / 1M
Context Window Maximum input + output tokens	1K tokens~2 A4 pages of text	2K tokens~3 A4 pages of text
Max Output Tokens Per single request	1K	2K
Throughput Speed Tokens generated per second	120 tok/s	45 tok/s
SWE-bench Verified Real-world software engineering	N/A	N/A

Siapa Unggul di Mana?

At-a-glance decision framework

Coding

Evaluations ongoing

Cost

Tied

Identical monthly runtime cost

Speed

GPT-2

+167% faster generation

Context

LLaMA-1 (65B)

2K tokens window

Skor Benchmark Terverifikasi

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

GPT-2LLaMA-1 (65B)

MMLU-Pro (Multi-task Language Understanding)

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

15.2%vs48%

LMSYS Chatbot Arena Elo

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

750ptsvs1020pts

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

120 tok/s vs45 tok/s

Latensi & Waktu Respons

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

GPT-20.30s

LLaMA-1 (65B)0.75s

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

GPT-24.47s

LLaMA-1 (65B)11.86s

Simulator Biaya Token Interaktif

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)

GPT-2 Monthly API Bill

$0.00 / month

$0/1M in · $0/1M out

LLaMA-1 (65B) Monthly API Bill

$0.00 / month

$0/1M in · $0/1M out

These models cost the same under this workload — no savings either way.Break-even

GPT-2 · Strengths & Key Advantages

Jendela konteks 1K dengan kapasitas output maksimum hingga 1K token (MMLU-Pro 15.2% · Arena Elo 750)
Kecepatan generasi tinggi 120 token/detik dengan latensi token pertama (TTFT) hanya 300 ms
Bobot terbuka (1.5B) yang siap di-hosting mandiri di GPU lokal atau cloud privat melalui vLLM dan Ollama

Considerations & Trade-offs

Membutuhkan infrastruktur GPU dengan kapasitas VRAM yang memadai untuk eksekusi lokal presisi penuh
Pada tugas pembuktian ilmiah tingkat ekstrem, model penalaran berat kelas atas memberikan kedalaman lebih tinggi

LLaMA-1 (65B) · Strengths & Key Advantages

Jendela konteks 2K dengan kapasitas output maksimum hingga 2K token (MMLU-Pro 48% · Arena Elo 1020)
Kecepatan generasi tinggi 45 token/detik dengan latensi token pertama (TTFT) hanya 750 ms
Bobot terbuka (65B (also 7B, 13B, 33B)) yang siap di-hosting mandiri di GPU lokal atau cloud privat melalui vLLM dan Ollama

Considerations & Trade-offs

Membutuhkan infrastruktur GPU dengan kapasitas VRAM yang memadai untuk eksekusi lokal presisi penuh
Pada tugas pembuktian ilmiah tingkat ekstrem, model penalaran berat kelas atas memberikan kedalaman lebih tinggi

Token Use & Task Economics

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

Metric	GPT-2	LLaMA-1 (65B)
Cost per Task Estimated USD to finish one task	$0.20	$0.20
Output Tokens / Task Tokens generated per task	24K	24K
Reasoning Tokens / Task Thinking tokens burned per task	0K	0K

Spesifikasi Teknis

Architecture, release timeline, capabilities, and modalities.

Feature	GPT-2	LLaMA-1 (65B)
Official API Model ID (SDK)	gpt-2	meta-llama/LLaMA-1-(65B)
API Protocol	OpenAI Responses API & Chat Completions v1	OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
Release Date	2019-02	2023-02
Knowledge Cutoff	2019	2022
Architecture	48-layer Decoder Transformer	Decoder-Only Transformer with RoPE & SwiGLU
Parameters	1.5B	65B (also 7B, 13B, 33B)
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)	Free across full context window (only KV-cache VRAM scales)	Free across full context window (only KV-cache VRAM scales)
Prompt Cache Policy & TTL	Automatic prefix KV-caching in vLLM / SGLang (0 cost)	Automatic prefix KV-caching in vLLM / SGLang (0 cost)
Computer Use / GUI Agent	Text-only completion (No GUI action loop)	Text-only completion (No GUI action loop)
MCP & Parallel Tool Calling	Prompt-based JSON extraction only	Prompt-based JSON extraction only
Web Search Grounding & Sandbox	Native Web Search tool + Hosted Code Interpreter & File Search RAG	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)	Text BPE (~4 chars/token)
Quantization & Min GPU VRAM	BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 2 GB VRAM (4-bit Quantized) · 4 GB VRAM (Native BF16)	BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 40 GB VRAM (4-bit Quantized) · 140 GB VRAM (Native BF16)
Safety & Frontier Classification	OpenAI Preparedness Framework Audited & System Card Published	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	text
Output Modalities	text	text

GPT-2 vs LLaMA-1 (65B): Jawaban Cepat (FAQ)

Which is more intelligent, GPT-2 or LLaMA-1 (65B)?

LLaMA-1 (65B) is more intelligent. It scores 25 compared with 12 on the composite Intelligence Index.

Which model is faster?

GPT-2 is faster, generating 120 tokens per second compared with 45 tokens per second.

Which model has lower latency?

GPT-2 has lower latency, with a time to first token of 0.30s compared with 0.75s.

Which model has a larger context window?

LLaMA-1 (65B) has a larger context window, supporting 2K tokens compared with 1K tokens.

Kesimpulan

Baik GPT-2 (Sangat cocok untuk self-hosting di server pribadi, fine-tuning, dan kedaulatan data penuh, sistem RAG perusahaan, dan integrasi API skala produksi.) maupun LLaMA-1 (65B) (Sangat cocok untuk self-hosting di server pribadi, fine-tuning, dan kedaulatan data penuh, sistem RAG perusahaan, dan integrasi API skala produksi.) sangat tangguh: LLaMA-1 (65B) unggul dalam penalaran dan pemrograman, GPT-2 memberikan kecepatan generasi token lebih tinggi, dan GPT-2 lebih hemat biaya untuk penggunaan API skala besar.

Pertanyaan Umum (FAQ)

Mana yang lebih baik untuk coding dan penalaran, GPT-2 atau LLaMA-1 (65B)?+

Dalam indeks kecerdasan gabungan dan benchmark coding, LLaMA-1 (65B) memimpin. Lihat skor SWE-bench dan GPQA di atas untuk detailnya.

Berapa perbandingan harga API GPT-2 vs LLaMA-1 (65B)?+

GPT-2 mengenakan biaya $0.00 / $0.00 per 1M token input/output, sedangkan LLaMA-1 (65B) sebesar $0.00 / $0.00. Secara keseluruhan, GPT-2 lebih hemat biaya.

Model mana yang memiliki jendela konteks lebih besar dan kecepatan lebih tinggi?+

GPT-2 mendukung konteks 1K token dibandingkan 2K token pada LLaMA-1 (65B), sementara GPT-2 unggul dalam kecepatan output token per detik.

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)

GPT-2 vs LLaMA-1 (65B)

Ganti & Bandingkan Model Apa Saja

GPT-2

LLaMA-1 (65B)

Siapa Unggul di Mana?

Skor Benchmark Terverifikasi

Latensi & Waktu Respons

Simulator Biaya Token Interaktif

GPT-2 · Strengths & Key Advantages

Considerations & Trade-offs

LLaMA-1 (65B) · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Spesifikasi Teknis

GPT-2 vs LLaMA-1 (65B): Jawaban Cepat (FAQ)

Kesimpulan

Pertanyaan Umum (FAQ)

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