Independent
Apodex 1.1Terbuka
Specialized open-weight coding and reasoning model based on optimized architecture.
Inteligensi
0.0 #765
Tingkat 100% teratas
Kecepatan output
145 t/s
ITL 6.9 ms/tok
Harga gabungan (3:1)
$0.35 /1M
Input $0.2/M · Output $0.8/M
Konteks
128K
≈ 328 halaman A4 · output maks 16,384
Quality Domain Radar
6-Axis Frontier Evaluation vs Category Average & Flagship
Apodex 1.1
Claude Mythos Preview (#1)
Average (68)
Sumbu radar diaproksimasi dari skor kategori jika pengukuran benchmark langsung tidak tersedia — lihat Metodologi.
Kelebihan & Trade-off
Di mana ia menang
- Open weights — self-host, fine-tune and audit with no vendor lock-in
- 145 tok/s output — fast enough for real-time agents
- Very low blended price — $0.35/1M mixed tokens
- Cheap prompt-cache reads at $0.02/1M
Kasus Penggunaan Killer
SWE-bench agents
Issue-to-PR resolution across multi-file repos — refactor, test and verify autonomously.
Quickstart Developer & API
Atur
HF_TOKEN dulu — dapatkan kunci APIcurl https://router.huggingface.co/v1/chat/completions \
-H "Authorization: Bearer $HF_TOKEN" \
-H "content-type: application/json" \
-d '{
"model": "apodex-1-1",
"messages": [{"role": "user", "content": "Refactor this function for O(n) time and explain the change."}]
}'import os
from openai import OpenAI
client = OpenAI(
base_url="https://router.huggingface.co/v1",
api_key=os.environ["HF_TOKEN"],
)
resp = client.chat.completions.create(
model="apodex-1-1",
messages=[{"role": "user", "content": "Refactor this function for O(n) time and explain the change."}],
)
print(resp.choices[0].message.content)const res = await fetch("https://router.huggingface.co/v1/chat/completions", {
method: "POST",
headers: {
Authorization: `Bearer ${process.env.HF_TOKEN}`,
"content-type": "application/json",
},
body: JSON.stringify({
model: "apodex-1-1",
messages: [{ role: "user", content: "Refactor this function for O(n) time and explain the change." }],
}),
});
console.log((await res.json()).choices[0].message.content);Sumber Daya & Tautan Resmi
Deployment API
Bandingkan host & latensi
Throughput, TTFT, dan harga cache di Groq, Cerebras, Together, DeepInfra, Fireworks, Bedrock, dan Azure.
GroqCerebrasTogether AIDeepInfraFireworks AIAWS BedrockAzure AI
Skor per sumber
Skor per kategori
Hasil benchmark
Spesifikasi Live & Arsitektur
Di balik kap
Dense · 72B
- Prompt caching supported — cached input reads at $0.02/1M tokens.
Tanggal rilis
20 Jul 2026
Arsitektur
Dense · 72B
Parameter
72B
Lisensi
Open Weights
Jendela konteks
131,072 tokens
Output maks
16,384 tokens
Modalitas
text
Harga cache
baca $0.02 · tulis $0.25 /1M
Penalaran
—
Harga input
$0.2/M
Harga output
$0.8/M
Kecepatan output
145 t/s
Waktu ke token pertama
—
Data diperbarui
26 Okt 2026
Estimasi tagihan bulanan
Estimasi pengeluaran bulanan
$0.00
Menghitung penghematan vs GPT-4o…
Kutip & sematkan
Badge Markdown GitHub
Loading badge markdown...BibTeX
@misc{llmpodium2026apodex11,
title = {Benchmark Analysis and Intelligence Evaluation of Apodex 1.1},
author = {LLMPodium Research},
year = {2026},
url = {https://llmpodium.com/models/apodex-1-1}
}Sematkan Lencana Skor
Tambahkan lencana Podium Score langsung ke README GitHub atau Hugging Face Anda — menautkan ke peringkat langsung.
Pratinjau
Markdown
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Loading badge snippet...Lainnya dari Independent
Model Alternatif
Alternatif terdekat untuk Apodex 1.1 berdasarkan kemampuan, harga, dan skor benchmark.