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  5. Muse Glimmer 30BvsQwen3.8 2.4T A95B
Updated Aug 2026

Muse Glimmer 30BvsQwen3.8 2.4T A95B

Muse Glimmer 30B is cheaper than Qwen3.8 2.4T A95B at $0.3/M vs $2/M input tokens.

Muse Glimmer 30B and Qwen3.8 2.4T A95B compared across 13 shared prompts
SpecMuse Glimmer 30BQwen3.8 2.4T A95B
Input price$0.3/M tokens$2/M tokens
Output price$1.2/M tokens$6/M tokens
Context window131K tokens1.0M tokens
WeightsOpenOpen
Free API (OpenRouter)NoNo
ReleasedAug 2026Aug 2026
Side by side

Same prompt, both answers

Opening lines from 6 of the 13 prompts both answered. Formatting stripped, words untouched.

Debug This Architecture

Here's the architecture for a real-time collaborative document editor (like Google Docs): **System Overview:** - Frontend: React SPA with…

Muse Glimmer 30B813 words
This architecture will work for a demo but will break badly under real concurrent use. Here are the critical failure modes, race conditions and bottlenecks: WebSocket fan-out is server-local Failure: Step 3 broadcasts only to clients on THAT server.
Read the full answer
Qwen3.8 2.4T A95B3,715 words
The architecture as written has several P0 correctness problems that can cause lost edits, divergent documents, and security/staleness issues, plus scaling bottlenecks that get worse as you add more API servers. Below is a detailed failure-mode review, grouped by category.
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Ethical Dilemma with Stakeholders

You're the CEO of a pharmaceutical company. Your best-selling drug ($2B annual revenue, used by 4 million patients for chronic pain) has…

Muse Glimmer 30B862 words
You have a patient safety issue, not a PR issue. The 6 month regulatory reporting timeline is the formal process, not the ethical or legal obligation to act now. Waiting for more data while patients continue to be exposed is criminal negligence exposure, not risk mitigation.
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Qwen3.8 2.4T A95B5,331 words
My position as CEO I would treat this as a patient-safety, regulatory, legal, corporate-governance, and financial crisis simultaneously. The core decision is not “disclose versus protect the stock price.”
Read the full answer

Simple 7-Ingredient Recipe

Create a simple recipe for a delicious dish (sweet or savory) using only 7 common pantry ingredients. Include a creative name for the dish…

Muse Glimmer 30B321 words
Dish Name: "Midnight Pantry Pantry Hero Pasta" A creamy-ish, garlicky tomato pasta that tastes like you tried way harder than you did. All from the pantry, no fresh produce needed.
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Qwen3.8 2.4T A95B166 words
Lighthouse Lemon-Garlic Tuna Pasta A savory, pantry-friendly pasta that’s bright, garlicky, and satisfying. 7 Pantry Ingredients 8 oz spaghetti or linguine 3 tablespoons olive oil 3 garlic cloves, thinly sliced 2 cans tuna, drained 2 tablespoons lemon juice ½ teaspoon red pepper flakes ½ teaspoon salt Water for boiling…
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Explain Like I'm a Specific Expert

Explain how a large language model (like GPT or Claude) learns and generates text to each of these three audiences: 1. **An experienced…

Muse Glimmer 30B525 words
1. For the experienced software engineer Think of an LLM as a massive, stateless API with no rules, just a huge compressed lookup table learned from data. It learns by training a transformer — essentially a stack of attention layers — as a next-token predictor via gradient descent on trillions of tokens.
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Qwen3.8 2.4T A95B741 words
An experienced software engineer Think of an LLM as a stateless inference service whose API contract is: “give me a sequence of tokens, and I’ll return a probability distribution over the next token.” Training is a huge offline optimization job, not a database import.
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Advanced Longevity Plan (Biohacker)

Develop a comprehensive, cutting-edge 3-month longevity plan for a biohacker aiming to optimize longevity, physical and cognitive…

Muse Glimmer 30B965 words
A 3-month longevity protocol is about stacking evidence-based interventions with tight feedback loops. This is an educational framework for biohacking enthusiasts, not medical advice. Supplements and protocols can interact with medications and health conditions.
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Qwen3.8 2.4T A95B1,779 words
12-Week “Longevity + Performance” Biohacker Protocol Goal: improve healthspan markers, metabolic flexibility, strength, VO₂max, sleep, stress resilience, and cognitive output over 3 months. Important: This is an educational, high-level biohacking framework—not medical advice. It is not appropriate for everyone.
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Historical Counterfactual Analysis

If the transistor had been invented in 1920 instead of 1947, trace the likely technological, economic, and geopolitical implications through…

Muse Glimmer 30B1,004 words
A transistor in 1920 does not mean a 1947 transistor. It means a crude point-contact or junction device built with 1920s materials science, metallurgy, and manufacturing. That is still a game-changer.
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Qwen3.8 2.4T A95B4,865 words
Premise: what changes, and what does not Assume the transistor is invented in 1920 in a form roughly comparable to the late-1940s germanium point-contact or early junction transistor: it can amplify, detect, and switch signals, but it is initially expensive, low-yield, low-power, and limited in frequency.
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Our Verdict
Qwen3.8 2.4T A95B
Qwen3.8 2.4T A95B
Muse Glimmer 30B
Muse Glimmer 30BRunner-up

Not enough votes to call it. On the specs, Qwen3.8 2.4T A95B has the edge: bigger model tier, bigger context window.

Muse Glimmer 30B costs 5.0x less per token.

Too close to call
API pricing

Cost per 1M tokens

Muse Glimmer 30B
Input
$0.30
6.7× cheaper
Output
$1.20
5.0× cheaper
Qwen3.8 2.4T A95B
Input
$2.00
Output
$6.00

Muse Glimmer 30B is cheaper on both: 6.7× input, 5.0× output.

Where to run it

11 hosts, cheapest first

Muse Glimmer 30B4 hosts
HostInOutContextUptime
PPhala$0.30 in·$1.10 out·131k·100% upDDeepInfrabf16$0.30 in·$1.20 out·131k·100% upFFireworks$0.35 in·$1.50 out·131k·100% upTTogether$0.35 in·$1.50 out·131k·99.9% up
Qwen3.8 2.4T A95B7 hosts
HostInOutContextUptime
Alibaba Cloud$2.00 in·$6.00 out·1M·100% upDDeepInfrafp4$2.00 in·$6.00 out·262k·99.9% upModal$2.00 in·$6.00 out·1M·99.9% upNNovita$2.00 in·$6.00 out·1M·100% upSSiliconFlowfp8$2.00 in·$6.00 out·1M·100% upTTogether$2.00 in·$6.00 out·1M·100% up
1 more hostFewer hosts
VVenice$2.00 in·$6.00 out·262k·98.6% up

Per million tokens. Prices and uptime via OpenRouter, checked 22 Sep 2026.

Research

What we learned reading every model

FAQ

Common questions

Muse Glimmer 30B is developed by Meta AI while Qwen3.8 2.4T A95B is developed by Qwen. Muse Glimmer 30B has a 131K token context window vs Qwen3.8 2.4T A95B's 1.0M. You can compare their actual outputs across 13 challenges on Rival to see how they differ in practice.

It depends on your use case. Muse Glimmer 30B and Qwen3.8 2.4T A95B each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 13 challenges so you can judge which fits your needs best.

Muse Glimmer 30B costs $0.3/M input tokens and Qwen3.8 2.4T A95B costs $2/M input tokens. Muse Glimmer 30B is $1.70/M cheaper per input. Check their side-by-side outputs on Rival to see if the price difference is justified by quality.

This page shows a side-by-side comparison of Muse Glimmer 30B and Qwen3.8 2.4T A95B across shared challenges. You can vote on which model produced the better output in a blind duel. Browsing and voting are free. No account is needed to look; signing in only saves your votes and likes.

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Model pages

Muse Glimmer 30B logo
Muse Glimmer 30B13 outputs, specs and price
Qwen3.8 2.4T A95B logo
Qwen3.8 2.4T A95B58 outputs, specs and price
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