Open Source

Quasar 438BOpen

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

#767released Aug 1, 2026·Open Weights·438B (38B active)
text128K ctxreasoning
API providersRun Model →Leaderboard
Intelligence
0.0 #767
Top 100% tier
Output Speed
95 t/s
ITL 10.5 ms/tok
Blended price (3:1)
$0.7 /1M
In $0.4/M · Out $1.6/M
Context
128K
≈ 328 A4 pages · max out 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)

Radar axes are approximated from category scores where direct benchmark measurements are missing — see Methodology.

Strengths & Trade-offs

Where it wins

  • 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

Killer Use Cases

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.

Developer Quickstart & API

Set HF_TOKEN first — get an API key
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."}]
  }'

Official Resources & Links

API deployment

Compare hosts & latency

Throughput, TTFT and cache pricing across Groq, Cerebras, Together, DeepInfra, Fireworks, Bedrock and Azure.

GroqCerebrasTogether AIDeepInfraFireworks AIAWS BedrockAzure AI
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Scores by Source

Category Scores

Benchmark Results

Live Specs & Architecture

Under the hood
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.
Release date
Aug 1, 2026
Architecture
Dense · 438B (38B active)
Parameters
438B (38B active)
License
Open Weights
Context Window
131,072 tokens
Max Output
32,768 tokens
Modalities
text
Cache Pricing
read $0.04 · write $0.5 /1M
Reasoning
Effort levels
Input Price
$0.4/M
Output Price
$1.6/M
Output Speed
95 t/s
Time to First Token
—
Data Updated
Oct 26, 2026

Estimated monthly bill

Estimated monthly spend
$0.00
Calculating savings vs GPT-4o...

Cite & embed

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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}
}

Embed Score Badge

Add a live Podium Score badge to your GitHub or Hugging Face README — it links back to the live ranking.

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Quasar 438B LLMPodium Score
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