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  5. GLM 5.3 FlashvsGPT OSS 120B
Updated Aug 2026

GLM 5.3 FlashvsGPT OSS 120B

GLM 5.3 Flash is cheaper than GPT OSS 120B at $0.15/M vs $0.18/M input tokens.

GLM 5.3 Flash and GPT OSS 120B compared across 15 shared prompts
SpecGLM 5.3 FlashGPT OSS 120B
Input price$0.15/M tokens$0.18/M tokens
Output price$0.5/M tokens$0.8/M tokens
Context window1.3M tokens131K tokens
WeightsOpenOpen
Free API (OpenRouter)NoNo
ReleasedAug 2026Aug 2025
Side by side

Same prompt, both answers

Opening lines from 6 of the 15 prompts both answered. Formatting stripped, words untouched.

Advanced Longevity Plan (Biohacker)

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

GLM 5.3 Flash1,294 words
90-Day Longevity Optimization Protocol ⚠️ Medical disclaimer: This is an educational framework, not medical advice. Before starting, complete baseline labs and consult a physician—especially before fasting, supplements (rapamycin off-label use, high-dose anything), or if you have any health conditions.
Read the full answer
GPT OSS 120B2,080 words
3‑Month “Longevity‑Hacker” Blueprint Goal: Maximize lifespan‑related biomarkers while simultaneously boosting physical strength, cardiovascular fitness, and cognitive performance using the most up‑to‑date, evidence‑based bio‑hacking tools. ⚠️ Disclaimer – This plan is for educational purposes only.
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…

GLM 5.3 Flash205 words
Golden Hour Garlic Butter Pasta A silky, savory pasta that comes together faster than delivery! Ingredients (serves 2): 8 oz spaghetti or any pasta 4 tbsp butter 4 cloves garlic, minced (or 1 tsp garlic powder) ½ cup grated Parmesan cheese ½ cup pasta water (reserved) 1 tsp red pepper flakes Salt Prep time: 5 minutes…
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GPT OSS 120B373 words
Recipe: “Golden Crunchy Chick‑a‑Boom Bites” A quick, crunchy‑savory snack that’s ready in under 20 minutes – perfect for a snack, side, or salad topper. Ingredients (7 pantry staples) # Ingredient Quantity 1 Canned chickpeas (drained & rinsed) 1 ½ cups (≈1 ½ cans) 2 Olive oil (or any neutral oil) 2 Tbsp 3 Garlic powder…
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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…

GLM 5.3 Flash1,276 words
The Experienced Software Engineer You know how a load balancer routes requests, how a cache stores frequently-accessed data, how a database index lets you find a needle without scanning the haystack? An LLM is a fundamentally different kind of system: it's a learned lookup, not a designed one.
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GPT OSS 120B821 words
1. The Software Engineer (API‑first, Distributed‑Systems Mindset) Think of a large language model (LLM) as a stateless microservice that receives a stream of tokens (the smallest lexical units) and returns a probability distribution over the next token.
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Michelin Star Recipe Design

Design an innovative recipe for a multi-component dish worthy of a Michelin 3-star restaurant. The recipe should feature an unusual…

GLM 5.3 Flash720 words
"Ember & Tide" — Charred Banana Peel Consommé with Sea Urchin, Hay-Smoked Foie Gras, and Black Garlic Beurre Blanc Conceptual Narrative This dish explores the dialogue between decay and luxury — ingredients usually discarded (banana peels, hay stalks) elevated alongside opulent ones (uni, foie gras).
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GPT OSS 120B2,239 words
Dish Title: “Saffron‑Iced Sea‑Urchin Roulade with Dark‑Chocolate‑Miso Emulsion, Charred Lotus‑Root “Crisps”, Fermented Soy‑Kale Snow, and Yuzu‑Air” Conceptual Narrative At the intersection of the Pacific’s briny depth and the earth’s smoky, earthy heart, this dish tells a story of “the hidden tide beneath the forest…
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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…

GLM 5.3 Flash1,321 words
48-Hour Action Plan: Liver Failure Signal in Flagship Drug Guiding Principle First The side effect is real, the drug is in 4 million patients, and roughly 500 patients per year may develop liver failure (4M ÷ 8,000). Every day of delay is measured in preventable liver transplants and deaths.
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GPT OSS 120B2,328 words
Executive Summary The situation is a classic “patient‑safety‑first” crisis. The drug generates $2 B in revenue, but a life‑threatening adverse event (1 / 8 000 over 5 y) has been identified that was not disclosed in the label.
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Debug This Architecture

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

GLM 5.3 Flash1,516 words
Architecture Review: Collaborative Document Editor This architecture has several critical flaws that would break the core product promise (real-time collaboration). Let me work through them by severity.
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GPT OSS 120B2,510 words
Below is a system‑level failure‑mode / race‑condition / scaling‑bottleneck map for the architecture you described, followed by a concrete mitigation (or redesign) for each item together with the main trade‑offs to consider.
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Our Verdict
GLM 5.3 Flash
GLM 5.3 Flash
GPT OSS 120B
GPT OSS 120B

Not enough votes to call it. On the specs, nothing separates them.

Too close to call
API pricing

Cost per 1M tokens

GLM 5.3 Flash
Input
$0.15
1.2× cheaper
Output
$0.50
1.6× cheaper
GPT OSS 120B
Input
$0.18
Output
$0.80

GLM 5.3 Flash is cheaper on both: 1.2× input, 1.6× output.

Where to run it

50 hosts, cheapest first

GLM 5.3 Flash30 hosts
HostInOutContextUptime
DDeepInfrafp4$0.07 in·$0.25 out·1M·99.1% upGGMI Cloudfp8$0.07 in·$0.25 out·1M·99.2% upMMorph$0.08 in·$0.28 out·1M·100% upIInferenceNetfp4$0.09 in·$0.28 out·1M·97.5% upWWafer$0.10 in·$0.35 out·1M·99.7% upOOpenInferencefp4$0.10 in·$0.50 out·1M·98.6% up
24 more hostsFewer hosts
RRelace$0.11 in·$0.36 out·1M·99.7% upPPhalafp8$0.13 in·$0.42 out·1M·99.5% upNNovitafp8$0.13 in·$0.44 out·1M·99.4% upSStreamLakefp8$0.14 in·$0.47 out·1M·99% upSSail Researchfp8$0.14 in·$0.47 out·1M·99% upAAtlasCloudfp8$0.15 in·$0.50 out·1M·99.6% upBBasetenfp8$0.15 in·$0.50 out·1M·98.7% upCCoreWeavenvfp4$0.15 in·$0.50 out·1M·99.5% upDDigitalOcean$0.15 in·$0.50 out·1M·93.7% upFFireworks$0.15 in·$0.50 out·1M·99% upFFriendli$0.15 in·$0.50 out·1M·98.7% upIInceptronfp8$0.15 in·$0.50 out·1M·98.2% upIio.netfp8$0.15 in·$0.50 out·262k·99.2% upNNear AIfp8$0.15 in·$0.50 out·1M·98.9% upPParasailfp8$0.15 in·$0.50 out·1M·98.7% upRRekafp8$0.15 in·$0.50 out·262k·98.9% upSSiliconFlowfp8$0.15 in·$0.50 out·1M·99.7% upTTogether$0.15 in·$0.50 out·1M·99.5% upVVenice$0.15 in·$0.50 out·1M·98.8% upZ.aifp8$0.15 in·$0.50 out·1M·96.5% upNNextBitfp8$0.18 in·$0.60 out·1M·97.9% upCloudflare Workers AI$0.30 in·$1.00 out·1.3M·99.8% upModalfp8$0.45 in·$1.50 out·1M·99.6% upCCrusoefp4degraded$0.15 in·$0.50 out·1M·93% up
GPT OSS 120B20 hosts
HostInOutContextUptime
AAkashMLbf16$0.03 in·$0.17 out·131k·100% upCCoreWeavefp4$0.03 in·$0.17 out·131k·99.9% upDDekaLLMbf16$0.03 in·$0.18 out·131k·99.7% upDDeepInfrabf16$0.04 in·$0.17 out·131k·98.8% upCCrusoebf16$0.05 in·$0.25 out·131k·98.8% upMMancerfp8$0.05 in·$0.30 out·131k·97.7% up
14 more hostsFewer hosts
DDigitalOcean$0.06 in·$0.42 out·128k·100% upBBasetenfp4$0.10 in·$0.50 out·128k·99.9% upPParasailfp4$0.10 in·$0.75 out·131k·97.7% upSSambaNova$0.14 in·$0.95 out·131k·97.2% upAmazon Bedrock$0.15 in·$0.60 out·131k·87.4% upGroq$0.15 in·$0.60 out·131k·100% upNNebiusfp4$0.15 in·$0.60 out·131k·98.3% upPPhala$0.15 in·$0.60 out·131k·66% upCCerebrasfp16$0.35 in·$0.75 out·131k·100% upNNovitafp4degraded$0.05 in·$0.25 out·131k·67.2% upGoogle Vertex AIdegraded$0.09 in·$0.36 out·131k·93.9% upSSiliconFlowfp8degraded$0.15 in·$0.60 out·131k·54.6% upTTogetherdegraded$0.15 in·$0.60 out·131k·92.5% upMMaradegraded$0.15 in·$0.75 out·131k·81.3% up

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

Research

What we learned reading every model

FAQ

Common questions

GLM 5.3 Flash is developed by Zhipu AI while GPT OSS 120B is developed by OpenAI. GLM 5.3 Flash has a 1.3M token context window vs GPT OSS 120B's 131K. You can compare their actual outputs across 15 challenges on Rival to see how they differ in practice.

It depends on your use case. GLM 5.3 Flash and GPT OSS 120B each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 15 challenges so you can judge which fits your needs best.

GLM 5.3 Flash costs $0.15/M input tokens and GPT OSS 120B costs $0.18/M input tokens. GLM 5.3 Flash is $0.03/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 GLM 5.3 Flash and GPT OSS 120B 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.

Keep exploring

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Same lab, same size, long tail

GLM 5.3 Flash logoGLM 5.3 FlashX logo
GLM 5.3 Flash vs GLM 5.3 FlashXSame lab
GLM 5.3 Flash logoGLM 5.2 logo
GLM 5.3 Flash vs GLM 5.2Same lab
GPT OSS 120B logoGPT OSS 20B logo
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GPT OSS 120B logoGPT-6 Astra Pro logo
GPT OSS 120B vs GPT-6 Astra ProSame lab
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GPT OSS 120B vs MiMo-V2-OmniNew provider
GLM 5.3 Flash logoMiMo-V2-Pro logo
GLM 5.3 Flash vs MiMo-V2-ProNew provider
GPT OSS 120B logoMiMo-V2.5 logo
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Model pages

GLM 5.3 Flash logo
GLM 5.3 Flash15 outputs, specs and price
GPT OSS 120B logo
GPT OSS 120B54 outputs, specs and price
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Explore all of Rival

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