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  5. DeepSeek R1 0528vsQwen3.8 Omni Flash
Updated Sep 2026

DeepSeek R1 0528vsQwen3.8 Omni Flash

DeepSeek R1 0528 is cheaper than Qwen3.8 Omni Flash at $0/M vs $0.15/M input tokens.

DeepSeek R1 0528 and Qwen3.8 Omni Flash compared across 9 shared prompts
SpecDeepSeek R1 0528Qwen3.8 Omni Flash
Input priceFree$0.15/M tokens
Output priceFree$0.47/M tokens
Context window164K tokens1.0M tokens
WeightsOpenClosed
Free API (OpenRouter)NoNo
ReleasedMay 2025Sep 2026
Side by side

Same prompt, both answers

Opening lines from 2 of the 9 prompts both answered. Formatting stripped, words untouched.

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…

DeepSeek R1 0528848 words
Here's how to explain LLM learning and generation to each audience, tailored to their perspective: For the Experienced Software Engineer (Skeptical about "Next Word Prediction") Focus: Systems analogy, emergent complexity, pattern recognition as understanding.
Read the full answer
Qwen3.8 Omni Flash913 words
For the experienced software engineer A large language model is best thought of as a gigantic, parameterized probabilistic function that maps a sequence of tokens to a probability distribution over the next token.
Read the full answer

Startup Pitch Teardown

Here's a pitch deck summary for a startup called "MindMeld AI": **Slide 1 - Vision:** "We're building the future of human-AI collaboration.…

DeepSeek R1 0528657 words
Here are the 3 weakest claims in the MindMeld AI pitch deck, why they are weak, and how to strengthen them: Weak Claim (Slide 3): "Our proprietary EEG headband uses advanced ML to decode neural patterns into text with 94% accuracy. Works with any language, any device."
Read the full answer
Qwen3.8 Omni Flash2,971 words
The three weakest claims—ranked by how likely they are to fail investor diligence—are: “94% accuracy… works with any language, any device.” “TAM: $180B” based on 3.5B smartphone users. “FDA clearance” consuming 40% of the Series A raise.
Read the full answer
Our Verdict
DeepSeek R1 0528
DeepSeek R1 0528
Qwen3.8 Omni Flash
Qwen3.8 Omni Flash

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

Too close to call
API pricing

Cost per 1M tokens

DeepSeek R1 0528
Input
$0.000
Output
$0.000
Qwen3.8 Omni Flash
Input
$0.15
Output
$0.47
Where to run it

5 hosts, cheapest first

DeepSeek R1 05284 hosts
HostInOutContextUptime
DDeepInfrafp4$0.50 in·$2.15 out·164k·99.9% upSSiliconFlowfp8$0.50 in·$2.18 out·164k·99.9% upSStreamLake$0.57 in·$2.29 out·128k·99.3% upNNovitafp8$0.70 in·$2.50 out·164k·99.5% up
Qwen3.8 Omni Flash1 host
HostInOutContextUptime
Alibaba Clouddegraded$0.15 in·$0.47 out·1M·99% up

Per million tokens. Prices and uptime via OpenRouter, checked 25 Sep 2026.

Research

What we learned reading every model

FAQ

Common questions

DeepSeek R1 0528 is developed by DeepSeek while Qwen3.8 Omni Flash is developed by Qwen. DeepSeek R1 0528 has a 164K token context window vs Qwen3.8 Omni Flash's 1.0M. You can compare their actual outputs across 9 challenges on Rival to see how they differ in practice.

It depends on your use case. DeepSeek R1 0528 and Qwen3.8 Omni Flash each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 9 challenges so you can judge which fits your needs best.

DeepSeek R1 0528 costs $0/M input tokens and Qwen3.8 Omni Flash costs $0.15/M input tokens. DeepSeek R1 0528 is $0.15/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 DeepSeek R1 0528 and Qwen3.8 Omni Flash 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

DeepSeek R1 0528 logo
DeepSeek R1 052858 outputs, specs and price
Qwen3.8 Omni Flash logo
Qwen3.8 Omni Flash9 outputs, specs and price
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