Comparison

SwiftRead vs LLM Convergence

Price, ratings, monetisation and update history for both apps, side by side — with what reviewers say about each.

Head to head
About

SwiftRead

Enhance your reading speed and comprehension with focus modes and natural text-to-speech narration. Import content from various sources and customize your reading experience across devices.

Highlights
  • Import PDFs, EPUBs, web articles
  • Visual focus modes (RSVP, pacing)
  • Human-like TTS narration (90+ languages)
  • Sync across devices
  • Customizable fonts, themes, speed
  • Works with Kindle Cloud Reader & Libby
Features
Read full description

Read any text up to 3X faster with research-backed visual and audio speed reading techniques, like RSVP and text-to-speech. Loved by students, professionals, and language-learners everywhere. Import text from PDFs, EPUBs, web articles, even external ebook readers like Kindle Cloud and Libby. Then read with visual focus modes or listen with human-like text-to-speech that improve reading speed, focus and comprehension. KEY FEATURES • Import documents in seconds — PDF, EPUB, web links, and pasted text • Works with web-based ebook readers — including Kindle Cloud Reader and Libby • Improve reading focus with research-backed visual reading modes — paced highlighting, different guided word displays, and RSVP with a patent pending eye anchor • Improve reading comprehension with natural text-to-speech — follow along with human-like text-to-speech and synced word highlighting in 90+ languages • Customize your reading experience — fonts, colors, spacing, and target reading speed • Sync across devices — pick up where you left off on phone, tablet, or computer PERFECT FOR • Finishing a long article PDF before a meeting • Getting through research papers for class • Improving reading fluency in a new language • Finally completing that ebook you started YOUR CONTENT, YOUR CONTROL • Your documents stay private. See swiftread.com/privacy for details. • Internet required for use. • Need help? Contact me (Troy, the developer) anytime at swiftread.com/help. PRICING SwiftRead is free to use within limits. Upgrade to Pro to remove limits and unlock advanced features. Payment charged to your Apple ID at confirmation. Cancel anytime in Settings. Terms of Use: https://swiftread.com/terms Privacy Policy: https://swiftread.com/privacy-policy

About

LLM Convergence

Features
Read full description

One AI model can be confidently wrong. LLM Convergence asks several at once and makes them reconcile. Pose a question and LLM Convergence sends it, in parallel, to a panel of leading AI models. A model you pick acts as the leader: it breaks every answer down into individual claims and reconciles them over a few rounds. What comes back is a single answer the panel converged on - plus a convergence score, and the specific points they disagreed on surfaced instead of buried. HOW IT WORKS - Ask in parallel - your prompt goes to several models at once, across OpenAI, Anthropic, Google, and fast open-model hosts. - Reconcile - a leader model decomposes each answer into claims and reconciles them round by round, so agreement is earned, not assumed. - See convergence - read one reconciled answer with a convergence score, and inspect the claims that didn't line up. TWO CONSENSUS MODES - Single judge - a leader model judges and reconciles each round. - Claim-commit voting - claims commit by panel quorum and stay committed (inspired by RAFT). GROUND ANSWERS IN THE WEB (OPTIONAL) Turn on grounding and LLM Convergence runs a web search before the panel answers, then puts the cited results in front of every model - so they reason over real sources instead of memory alone. Grounded answers come back with tappable [S1]-style citations and a Sources list, a grounding score next to the convergence score, and an honest "couldn't ground this" when a search turns up nothing. It uses a frontier key you already have (Claude, Gemini, or an OpenRouter model) - no separate search key, and it works on every platform. FACT-CHECK MODE Ask LLM Convergence to fact check something and it switches from answering to verifying. Paste a link and it opens the page - or check pasted text, a bare claim, or the answer it just gave you. It pulls out the checkable claims, runs a separate web search for each one, has the whole panel weigh the evidence, and returns a verdict per claim - supported, refuted, partly supported, or unverifiable - with citations you can tap. It reads how you phrased the question, so there is no mode to switch on. Fact-check mode needs a model that can search the web. BRING YOUR OWN KEYS Use your own provider API keys. They're stored securely in your device's keychain and used only to call the providers you choose - never sent to us. One key per provider: add more models from a vendor you've already set up without re-pasting its key, or override the key for a specific model. Mix and match models, run more than one model from the same vendor, and pin whichever one leads. PRIVATE BY DESIGN LLM Convergence is a pure client - there's no account and no server of ours. - No analytics, no telemetry, no ad SDKs. - Prompts go straight from your device to the providers you configured. - Chat history is saved locally and stays on your device. Delete any conversation anytime. YOU'RE IN CONTROL Choose which models sit on the panel, which one leads, how many rounds run, and the convergence threshold. Multi-turn chat with local history and Markdown-rendered answers. Run more than one conversation at a time - a chat keeps working in the background while you read another. Supported providers: OpenAI, Anthropic (Claude), Google (Gemini), and OpenAI-compatible hosts including Groq, Fireworks, Cerebras, and OpenRouter - the last reaching many models behind a single key - with free open models available. Note: LLM Convergence requires your own API keys from the providers you want to use. Provider usage is billed by those providers per their own pricing.

Screenshots

SwiftRead4 screens
LLM Convergence4 screens

Verdict

The call

The clearest difference is update cadence: SwiftRead at every 9 days against LLM Convergence's every 3 weeks. LLM Convergence's advantage is iOS requirement (13.0 vs 15.1). On price, ads, in-app purchases and device support there is nothing between them.

Scored on Price · Rating · Positive reviews · Number of ratings · Update frequency · Ads · In-app purchases · Monetization · Best chart rank · Devices · Requires iOS

CostPrice · In-app purchases · Ads · Monetization

Both are free to download. SwiftRead sells 3 in-app purchases, starting at $19.99 per month and LLM Convergence sells 1 one-off in-app purchase. Whichever you choose, the download price is not the number that matters.

UpkeepUpdate frequency

SwiftRead ships an update every 9 days, LLM Convergence every 3 weeks. Both last shipped on October 25, 2026.

Scorecard2 real differences · 8 level
SwiftRead versus LLM Convergence: the parameters behind the verdict, then further details
ParameterSwiftReadLLM Convergence
PriceFreeFree
Rating4.2 (38 ratings) — better—
Positive reviews84.6% of reviews—
Number of ratings38 — better—
Update frequencyEvery 9 days — betterEvery 3 weeks
AdsNoNo
In-app purchasesYesYes
MonetizationFreemium—
DevicesiPhone, iPad, iPodiPhone, iPad, iPod, Mac — better
Requires iOS15.113.0 — better
Further details — not scored
Size72 MB25 MB
Age rating4+9+
DeveloperSwiftReadIlya Obshadko

In-app purchases

3 purchases

SwiftRead

Subscriptions3
  • Monthly$19.991 Month
  • Quarterly$44.993 Months
  • Annual$119.991 Year
1 purchases

LLM Convergence

One-time1
  • LLM Convergence Pro$6.29

Questions

Is SwiftRead free?
SwiftRead is free to download, with in-app purchases available.
Is LLM Convergence free?
LLM Convergence is free to download, with in-app purchases available.
Do SwiftRead or LLM Convergence have ads?
Neither SwiftRead nor LLM Convergence shows ads.
Which is updated more often, SwiftRead or LLM Convergence?
SwiftRead ships an update every 9 days, and LLM Convergence every 3 weeks. Most recently, SwiftRead was updated on October 25, 2026 and LLM Convergence on October 25, 2026.

Other comparisons