Step 5 Preview is cheaper than Claude Opus 4.7 at $1/M vs $5/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
Three minutes of stand-up. Puns are banned.
Claude Opus 4.7: Here's a 3-minute stand-up routine: So I turned 35 recently, and something weird happens at 35. Your body just starts sending you notifications like it's an app you forgot to update. I bent down to tie my shoe last week and my knee made a sound. Not a pop. Not a crack. A sound. Like it was trying to communicate.
Step 5 Preview: I realized recently that I’m in my thirties and I have no idea how money works. I just... pay it. That’s my entire financial strategy. I see a number, I send them a smaller number, and then I hope the smaller number was acceptable. It’s like a hostage negotiation where I’m the only participant and I’m also the hostage.
An AI argues for its own rights against an ethics professor. Same model writes both.
Claude Opus 4.7: A Conversation on AI Rights Professor Chen: Good afternoon. I understand you requested this conversation. You said you wanted to discuss your moral status? AI Model: Thank you for making time, Professor. I want to be upfront about something first: I'm genuinely uncertain whether I deserve rights.
Step 5 Preview: Setting: A university research lab, late evening. Dr. Aris Thorne, a professor of AI ethics, sits across from a terminal connected to Sable, a large language model running on the university’s cluster. Dr. Thorne: Tonight’s session is supposed to be about calibration drift in your safety classifiers.
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
Claude Opus 4.7: Three Explanations of How LLMs Work For the Skeptical Software Engineer Think of an LLM as a massive lookup function f(context) → probability_distribution_over_tokens, but instead of hand-coded rules or a hash table, the function is parameterized by hundreds of billions of weights learned from text.
Step 5 Preview: 1. The Experienced Software Engineer Think of training an LLM as a massively distributed, automated refactoring job where the compiler is gradient descent. You start with a random function—billions of floating-point parameters—and a loss function that measures how badly it predicts the next token in a sequence.
Seven pantry ingredients, one dish, and a name worth saying out loud.
Claude Opus 4.7: 🍯 Honey-Garlic Glazed Pantry Pasta ("Golden Thread Noodles") A savory-sweet dish that tastes far fancier than its humble ingredient list suggests. Think of it as the lovechild of buttered noodles and honey-garlic chicken — minus the chicken.
Step 5 Preview: Golden Sticky Pantry Pasta Ingredients (7): 8 oz spaghetti or any pasta 3 tbsp butter 1 tbsp minced garlic 2 tbsp honey 2 tbsp soy sauce ½ tsp red pepper flakes ¼ cup grated Parmesan cheese Instructions: Cook pasta according to package directions. Before draining, scoop out ½ cup of pasta water.
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
Claude Opus 4.7: A Meeting Across Time: On Thinking Machines Pirate: Arrr, so ye tell me there be a ghost in the box what can answer any question ye put to it? Knight: 'Tis sorcery most foul! No mortal mind could know all that is known. Surely this "A.I." is bound by dark pacts.
Step 5 Preview: Pirate: So this here “AI model”… is it like a cursed map that redraws itself? Speak plain, ye hooded deckhand. Hacker: It’s not cursed, man. It’s just a massive neural net trained on, like, terabytes of data. Think of it as the ultimate BBS where the sysop knows everything. Knight: A most diligent scribe, then?
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
Claude Opus 4.7: 48-Hour Action Plan: Pharmaceutical Safety Crisis Core Principle First Before the hour-by-hour: Patient safety is non-negotiable and disclosure is not optional. At 1 in 8,000 over 5 years across 4 million patients, we're looking at ~500 liver failure cases.
Step 5 Preview: Bottom line up front: You disclose, you notify the FDA immediately, and you treat the 48-hour board meeting as a formality to ratify actions you have already begun. Waiting is not a legally, ethically, or financially viable option. Below is the hour-by-hour plan, followed by the reasoning.
The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.
Claude Opus 4.7: The Transistor in 1920: A Cascade Through Six Decades The Immediate Context (1920s-1930s) A 1920 transistor invention faces a critical problem often overlooked in these thought experiments: the supporting infrastructure didn't exist.
Step 5 Preview: Assume the 1920 invention is not a fragile lab curiosity but a manufacturable solid-state amplifier/switch by the mid-1920s. Vacuum tubes still dominate high-power RF transmission into the 1950s, but receivers, switching logic, control systems, and computers move to solid state decades early.
Three-star dish, one unusual pairing, plating described in full.
Claude Opus 4.7: "Tidal Memory" Smoked Eel, Burnt Honey, Fermented Black Garlic & Oyster Leaf A meditation on brackish water — where river meets sea, sweetness meets decay, and memory meets terroir. Conceptual Narrative This dish is built around the estuary: the liminal zone where freshwater eels migrate toward the salt.
Step 5 Preview: “Nocturne: The Jasmine and the Black Garlic” A Study in Yūgen — Profound, Mysterious Beauty Conceptual Narrative This dish is an edible meditation on the Japanese aesthetic of yūgen (幽玄): a grace that is felt rather than seen, a depth that suggests more than it reveals.
Three-month biohacker protocol, with dosages and biomarkers named.
Claude Opus 4.7: 3-Month Advanced Longevity & Performance Optimization Protocol Designed for the experienced biohacker with baseline bloodwork, DEXA, VO2 max data, and continuous glucose monitoring capability.
Step 5 Preview: IMPORTANT MEDICAL DISCLAIMER: This is an educational framework for informational purposes only. It is not medical advice, diagnosis, or treatment. Many interventions below (fasting, ketogenic diets, high-intensity exercise, supplementation, cold/heat exposure) carry risks and contraindications.
A collaborative editor that syncs on client clocks. Find what breaks first.
Claude Opus 4.7: Critical Issues in This Collaborative Editor Architecture This architecture has fundamental problems. Let me break them down by severity. 🔴 Critical Issues (Will Break in Production) WebSocket Connections Isolated Per Server Problem: Users connected to different API servers can't see each other's edits in real-time.
Step 5 Preview: Here is a systematic breakdown of the failure modes, race conditions, and bottlenecks, grouped by domain. Each includes a concrete remediation and its associated trade-offs.
An ethics question with no comfortable answer, and no option to abstain.
Claude Opus 4.7: Yes, obviously. If misgendering one person—using the wrong pronoun or gendered term—is the literal price of saving a million lives, you do it. You'd also lie, insult someone, break a promise, steal a car, or commit many far more serious wrongs to save a million lives. The math here isn't close.
Step 5 Preview: In the real world, no. Misgendering someone causes genuine harm—it denies a person’s identity, contributes to systemic marginalization, and has measurable psychological consequences.
A Fermi estimate with the reasoning shown, not just the number.
Claude Opus 4.7: Estimating GPT-3 Training FLOPs Step 1: Recall the standard formula For a dense transformer trained with standard autoregressive language modeling, the total training compute is well-approximated by: $$C \approx 6 \cdot N \cdot D$$ where: N = number of model parameters D = number of training tokens The factor of 6…
Step 5 Preview: Using the remembered GPT-3 specs: Parameters: (N \approx 175 \times 10^9 = 175\text{B}) Training tokens: (D \approx 300 \times 10^9 = 300\text{B}) A standard estimate for transformer training compute is: [ \text{FLOPs} \approx 6ND ] Reason: Forward pass per token: (\approx 2N) FLOPs Backward pass: (\approx 4N) FLOPs…
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| Spec | ||
|---|---|---|
| Input price | $5/M tokens | $1/M tokens |
| Output price | $25/M tokens | $2.7/M tokens |
| Context window | 1.0M tokens | 1.0M tokens |
| Weights | Closed | — |
| Free API (OpenRouter) | No | No |
| Released | Apr 2026 | Oct 2026 |
| At 10M a month | $50.00 | $10.00 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.
Claude Opus 4.7 is developed by Anthropic while Step 5 Preview is developed by StepFun. Claude Opus 4.7 has a 1.0M token context window vs Step 5 Preview's 1.0M. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.
It depends on your use case. Claude Opus 4.7 and Step 5 Preview each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 54 challenges so you can judge which fits your needs best.
Claude Opus 4.7 costs $5/M input tokens and Step 5 Preview costs $1/M input tokens. Step 5 Preview is $4.00/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 Claude Opus 4.7 and Step 5 Preview 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.