Open Source

Quasar 438BTerbuka

Massive Mixture-of-Experts open-weight model with 38B active parameters per token.

#767dirilis 1 Agu 2026·Open Weights·438B (38B active)
text128K ctxpenalaran
Penyedia APIJalankan Model →Peringkat
Inteligensi
0.0 #767
Tingkat 100% teratas
Kecepatan output
95 t/s
ITL 10.5 ms/tok
Harga gabungan (3:1)
$0.7 /1M
Input $0.4/M · Output $1.6/M
Konteks
128K
≈ 328 halaman A4 · output maks 32,768

Quality Domain Radar

6-Axis Frontier Evaluation vs Category Average & Flagship

Quasar 438B
Claude Mythos Preview (#1)
Average (68)
Coding (68)Mathematics (70)Hard Science (GPQA) (71)Agentic & Tool Use (63)Knowledge (MMLU) (65)Vision / Multimodal (25)

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
  • Very low blended price — $0.7/1M mixed tokens
  • Cheap prompt-cache reads at $0.04/1M
  • Reasoning mode with adjustable effort levels

Kasus Penggunaan Killer

Math & proof work
Step-verified reasoning for olympiad math, theorem proving and formal verification.
On-prem deployment
Air-gapped and regulated-environment serving on your own hardware.

Quickstart Developer & API

Atur HF_TOKEN dulu — dapatkan kunci API
curl https://router.huggingface.co/v1/chat/completions \
  -H "Authorization: Bearer $HF_TOKEN" \
  -H "content-type: application/json" \
  -d '{
    "model": "quasar-438b",
    "messages": [{"role": "user", "content": "Refactor this function for O(n) time and explain the change."}]
  }'

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
Lihat matriks penyedia →

Skor per sumber

Skor per kategori

Hasil benchmark

Spesifikasi Live & Arsitektur

Di balik kap
Dense · 438B (38B active)
  • Switchable reasoning effort — trading latency and tokens for accuracy on hard problems.
  • Prompt caching supported — cached input reads at $0.04/1M tokens.
Tanggal rilis
1 Agu 2026
Arsitektur
Dense · 438B (38B active)
Parameter
438B (38B active)
Lisensi
Open Weights
Jendela konteks
131,072 tokens
Output maks
32,768 tokens
Modalitas
text
Harga cache
baca $0.04 · tulis $0.5 /1M
Penalaran
Level effort
Harga input
$0.4/M
Harga output
$1.6/M
Kecepatan output
95 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
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BibTeX
@misc{llmpodium2026quasar438b,
  title = {Benchmark Analysis and Intelligence Evaluation of Quasar 438B},
  author = {LLMPodium Research},
  year = {2026},
  url = {https://llmpodium.com/models/quasar-438b}
}

Sematkan Lencana Skor

Tambahkan lencana Podium Score langsung ke README GitHub atau Hugging Face Anda — menautkan ke peringkat langsung.

Pratinjau
Quasar 438B LLMPodium Score
Markdown
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