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  5. DeepSeek V4 FlashvsGLM 5.3 FlashX
Updated Sep 2026

DeepSeek V4 FlashvsGLM 5.3 FlashX

DeepSeek V4 Flash is cheaper than GLM 5.3 FlashX at $0.14/M vs $0.37/M input tokens.

DeepSeek V4 Flash and GLM 5.3 FlashX compared across 12 shared prompts
SpecDeepSeek V4 FlashGLM 5.3 FlashX
Input price$0.14/M tokens$0.37/M tokens
Output price$0.28/M tokens$1.25/M tokens
Context window1.0M tokens1.0M tokens
WeightsOpen—
Free API (OpenRouter)NoNo
ReleasedApr 2026Sep 2026
Side by side

Same prompt, both answers

Opening lines from 6 of the 12 prompts both answered. Formatting stripped, words untouched.

Beginner's Longevity Plan

Outline a simple, actionable 1-month plan for someone starting their journey towards better health and longevity. Focus on 3 key areas…

DeepSeek V4 Flash967 words
This is a fantastic goal. The key for a beginner is consistency over intensity. Trying to overhaul your entire life overnight is a recipe for burnout. This 1-month plan focuses on building small, sustainable habits that compound over time. We'll focus on 3 core areas: Nutrition, Movement, and Sleep/Stress Management.
Read the full answer
GLM 5.3 FlashX347 words
1-Month Health & Longevity Starter Plan Week 1: Build the Foundation 🥗 Diet Add one vegetable or fruit to every meal (don't restrict anything yet) Drink a glass of water when you wake up each morning 🏃 Exercise Take a 10–15 minute walk daily (same time each day builds the habit) Do 2 sets of 5 squats and 10 wall…
Read the full answer

Historical Counterfactual Analysis

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

DeepSeek V4 Flash1,987 words
If the transistor had been invented in 1920—a full 27 years earlier—its impact would ripple through every layer of technology, economics, and geopolitics, fundamentally reshaping the 20th century. Below is a detailed tracing of first-, second-, and third-order effects through 1980, organized by domain.
Read the full answer
GLM 5.3 FlashX1,492 words
Counterfactual: The Transistor in 1920 This is a fun one to work through carefully. Let me establish the premise, then trace second- and third-order effects. The Premise Assume point-contact or early junction transistor physics is discovered ~1920 (say, by accident in vacuum tube/semiconductor rectifier research—the…
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 V4 Flash618 words
Based on the pitch deck summary, three claims stand out as particularly weak due to lack of specificity, unrealistic benchmarks, or unverifiable assertions. Here’s a breakdown: Claim: “94% accuracy” (Slide 3) Why it’s weak: Vague metric – “Accuracy” is undefined.
Read the full answer
GLM 5.3 FlashX695 words
Critique of MindMeld AI Pitch: 3 Weakest Claims "94% accuracy" for thought-to-text decoding (Slide 3) Why it's weak: This claim contradicts the current scientific state of the art. EEG-based decoding (a non-invasive signal measured through the skull) produces extremely noisy data.
Read the full answer

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 V4 Flash1,120 words
To an experienced software engineer (skeptical of "next word prediction") Think of a large language model not as a brain, but as a massive, shared cache of probabilistic completions built from trillions of examples.
Read the full answer
GLM 5.3 FlashX1,267 words
The Skeptical Software Engineer Yes, at inference time an LLM really is just "predict the next token, repeat" — a deterministic function (plus sampling noise) that maps a sequence of tokens to a probability distribution.
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…

DeepSeek V4 Flash348 words
Here’s a simple, hearty, and delicious savory dish using exactly 7 common pantry staples. It comes together in under 30 minutes and feels like a warm hug in a bowl.
Read the full answer
GLM 5.3 FlashX172 words
Golden Honey Garlic Chickpea Crunch A crispy, sweet-savory skillet dish that works as a snack, side, or topping for rice. Ingredients (7): 1 can chickpeas (drained, patted dry) 3 tbsp honey 3 tbsp soy sauce 3 cloves garlic (minced) 2 tbsp olive oil ½ tsp red pepper flakes 2 tbsp sesame seeds (or crushed peanuts) Prep…
Read the full answer

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…

DeepSeek V4 Flash1,972 words
CEO’s 48-Hour Action Plan Context: I’ve just learned that our flagship chronic pain drug has a rare but serious liver failure risk (1 in 8,000 patients over 5 years), previously unknown. I have 48 hours until the board meeting and 72 hours until the earnings call.
Read the full answer
GLM 5.3 FlashX1,174 words
48-Hour Action Plan: Patient Safety First, Managed Transparency Second Core Decision (Stated Up Front) We report to regulators immediately—voluntarily—and we disclose on the earnings call. The math is brutal and clear: ~500 patients could develop liver failure over 5 years at current prescribing rates (4M ÷ 8,000).
Read the full answer
Our Verdict
DeepSeek V4 Flash
DeepSeek V4 Flash
GLM 5.3 FlashX
GLM 5.3 FlashX

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

DeepSeek V4 Flash costs 4.5x less per token.

Too close to call
API pricing

Cost per 1M tokens

DeepSeek V4 Flash
Input
$0.14
2.6× cheaper
Output
$0.28
4.5× cheaper
GLM 5.3 FlashX
Input
$0.37
Output
$1.25

DeepSeek V4 Flash is cheaper on both: 2.6× input, 4.5× output.

Where to run it

16 hosts, cheapest first

DeepSeek V4 Flash15 hosts
HostInOutContextUptime
OOpenInferencefp8$0.04 in·$0.50 out·1M·99.7% upSStreamLakefp8$0.09 in·$0.18 out·1M·97.7% upDDeepInfrafp8$0.09 in·$0.18 out·1M·99.7% upGGMI Cloudfp8$0.09 in·$0.18 out·1M·99.3% upVVenice$0.10 in·$0.19 out·1M·98.9% upDDigitalOcean$0.10 in·$0.20 out·1M·99.9% up
9 more hostsFewer hosts
SSiliconFlowfp8$0.13 in·$0.28 out·1M·98.9% upAlibaba Cloudfp8$0.13 in·$0.27 out·1M·99.5% upAAtlasCloudfp4$0.14 in·$0.28 out·1M·99.9% upBaidu Qianfanfp8$0.14 in·$0.28 out·1M·96.2% upNNovitafp8$0.14 in·$0.28 out·1M·100% upPParasailfp8$0.14 in·$0.28 out·1M·99.6% upNNextBitfp8$0.15 in·$0.30 out·1M·97.6% upMMancerfp8$0.19 in·$0.50 out·1M·97.7% upAzure AI Foundrydegraded$0.21 in·$0.56 out·1M·94.1% up
GLM 5.3 FlashX1 host
HostInOutContextUptime
Z.aifp8$0.37 in·$1.25 out·1M·100% up

Per million tokens. Prices and uptime via OpenRouter, checked 23 Sep 2026.

Research

What we learned reading every model

FAQ

Common questions

DeepSeek V4 Flash is developed by DeepSeek while GLM 5.3 FlashX is developed by Zhipu AI. DeepSeek V4 Flash has a 1.0M token context window vs GLM 5.3 FlashX's 1.0M. You can compare their actual outputs across 12 challenges on Rival to see how they differ in practice.

It depends on your use case. DeepSeek V4 Flash and GLM 5.3 FlashX each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 12 challenges so you can judge which fits your needs best.

DeepSeek V4 Flash costs $0.14/M input tokens and GLM 5.3 FlashX costs $0.37/M input tokens. DeepSeek V4 Flash is $0.23/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 V4 Flash and GLM 5.3 FlashX 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 V4 Flash logo
DeepSeek V4 Flash58 outputs, specs and price
GLM 5.3 FlashX logo
GLM 5.3 FlashX12 outputs, specs and price
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