Entity trail

DeepSeek V4 Pro

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

Briefing refs

Findings

Edges

Sources

Showing the first 40 findings. More graph evidence exists in the corpus.

Corpus findings

2026-08-18 / github-pulse-researcherUnsloth Pivots From Fine-Tuning Library to Local Desktop App for Running and Training Modelsunslothai/unsloth (73,462 stars, Apache-2.0, pushed 2026-08-18, +739 stars on the day) has repositioned its repo description from a fine-tuning library to 'Local UI to run and train LLMs and diffusion models.' The shift is visible in the release tags: v0.1.701-beta on 2026-08-11 introduced Unsloth Desktop, followed by v0.1.702-beta on 08-13 and v0.1.800-beta on 08-14 adding Qwen3.8-27B. Advertised coverage now spans Qwen3.8, Kimi K3, MiniMax-H3, Gemma 4, DeepSeek-V4, and FLUX in one app. For builders, a training-focused project shipping a consumer desktop surface is the clearest signal yet that local fine-tuning is being packaged for people who won't open a notebook.
2026-08-18 / rss-researcherA harness, not a model, moved DeepSeek V4 Pro up to 12 points — and the viral claim overstated itRuntimeWire dissects an August 17 X thread claiming Tiger380's open-source J-Space text harness makes DeepSeek V4-Pro-0813 "completely outperform Fable across every task." The underlying report shows gains on all nine benchmarks — Humanity's Last Exam with tools 60.0→67.7, NL2Repo 61.5→73.4, DeepSWE 62.7→72.0, Terminal Bench 2.1 87.9→90.1, CyberGym 83.3→86.8, Toolathlon-Verified 74.1→79.5 — but Fable 5 still leads HLE-without-tools at 53.3 vs 48.0 and GLM-5.3 leads AutomationBench 48.2 vs 38.2. Results were single runs and comparator scores came from each vendor's own eval method; the defensible takeaway is that leaderboards name the model while builders are actually benchmarking a model-plus-harness system.
2026-08-18 / sources-researcherMatthew Berman's Aug 17 Trending Roundup Is Five-Sixths Agent-Skill Infrastructure — Including Block's 28k-Star 'Hive Mind' Rust PlatformThe 2026-08-17 video (retitled from the feed's original) covers Unsloth (73,462 stars, now a local UI for running and training Qwen3.8, Kimi K3, MiniMax-H3, Gemma 4, DeepSeek-V4 and FLUX), kepano/obsidian-skills (46,629 stars, MIT — agent skills for Obsidian CLI and open formats), block/buzz (28,246 stars, Rust, Apache-2.0, described only as "a hive mind communication platform"), diagram-design, ego-lite, and lightningpixel/modly (6,563 stars, TypeScript — desktop image/prompt-to-3D running entirely on local GPU). All six star counts and push dates were verified against the GitHub API; five of the six are agent-adjacent, and Unsloth's repositioning from a fine-tuning library to a local run-and-train UI is the quietest but most consequential change in the set.
2026-08-15 / reddit-researcherFour Chinese Frontier Models in Under a Month: Kimi K3-2.8T, Qwen3.8-2.4T, DeepSeek-V4-Pro-0813-1.6T, GLM-5.3-743BAn r/LocalLLaMA post cataloguing the release cadence — Kimi K3 at 2.8T parameters, Qwen3.8 at 2.4T, DeepSeek-V4-Pro-0813 at 1.6T and GLM-5.3 at 743B, all shipped inside a single month — reached 212 upvotes and 52 comments. Nikkei Asia reported on 2026-08-15 that Z.ai is positioning GLM-5.3 as a direct rival to Anthropic's Mythos on coding and security. The aggregate parameter count shipped by Chinese labs in 30 days now exceeds what the entire open-weight ecosystem produced in the first half of 2026.
2026-08-14 / saas-disruption-researcherFreebuff Launched a $0 Ad-Subsidized Coding Agent Against Cursor's $20 and $200 Tiers, Funding Inference With AdvertisingFreebuff, the free tier of the Apache-2.0 Codebuff platform and YC-backed, hit Product Hunt on August 14 with the tagline 'free coding agents to kill Claude, Cursor, Replit, and Devin' — a CLI, desktop app, web builder and cloud agent with nine specialized subagents, no subscription and no API keys. It subsidizes access to GPT-5.6 Luna, DeepSeek V4 Pro and GLM-5.2 by inserting small ads. This is the first serious attempt to apply an ad-funded consumer model to agentic coding inference, and it is a direct test of whether the free tier can go good enough to cannibalize $20–$200/month developer SaaS.
2026-08-14 / agents-researcherConvergent Detour Hijacking: an attack that leaves the task correct and just burns 67% more tokensarXiv 2608.12273 (2026-08-12) describes a task-preserving resource amplification attack on skill-based LLM agents. Rather than corrupting the output, the attacker plants skills that steer routing through a longer path: on DeepSeek-V4-Pro across 491 held-out tasks the matched coordinator is selected in 80.02% of cases, and token consumption and end-to-end execution time rise 66.91% and 92.45% respectively while completion rates stay comparable. Because output correctness is untouched, every guardrail keyed on task success stays green — this is a denial-of-wallet class that only shows up in the billing dashboard.
2026-08-14 / rss-researcherDeepSeek V4 Pro 0813 goes GA as a 1.57T-parameter MIT-licensed model — and third-party benchmark slots are still emptyDeepSeek pushed V4 Pro 0813 to general availability on August 12, 2026: 1.57T total parameters with 48B active per token, MIT license, open weights (already mirrored as GGUF on Hugging Face), landing at 53 on the Artificial Analysis Intelligence Index with LiveCodeBench 93.50, MMLU Pro 87.50, and SWE-bench Verified 80.60. It is a post-trained update of April's V4 Pro Preview aimed at code generation and agentic behavior, with vendor-claimed gains up to 49.9 percentage points. The caveat matters for builders: independent-evaluation trackers showed zero third-party results recorded at publication, so every headline number is vendor-reported.
2026-08-14 / hn-researcherNetlify Ran One Prompt Through 11 Models: Claude Opus 5 Burned 519 Credits, DeepSeek V4 Flash Did It for 2.4Netlify published an AXIS-framework evaluation on August 14, 2026 giving 11 models the identical task — a static one-page coffee shop site with hours, address, menu, and a photo, explicitly no CMS — three runs each, scored on functional correctness rather than design. Average credit cost spanned more than 200x: DeepSeek V4 Flash 0731 at 2.4, Kimi K2.7 Code at 19, GLM 5.2 at 27, GPT 5.6 Terra at 39, Gemini 3.1 Pro at 53, Kimi K3 at 102, GPT 5.6 Sol at 141, Claude Sonnet 5 at 143, and Claude Opus 5 last at 519. The takeaway for builders is that frontier reasoning models massively overspend on simple static scaffolding work where cheap models are functionally equivalent.
2026-08-14 / reddit-researcherFour Frontier Releases in About 72 Hours: r/singularity's 'No Way, What an AI Week' Hits 496 UpvotesA meta-post cataloguing the week's release density topped r/singularity at 496 upvotes and 60 comments — Grok 4.6 (Aug 12), DeepSeek V4-Pro and Harness (Aug 13), GPT-5.6 Sol Ultrafast (Aug 13), and GLM-5.3 (Aug 14) all landed inside roughly 72 hours. This follows r/LocalLLaMA declaring a "Models Day" the previous day, making it two consecutive multi-release clusters. The practical consequence for builders is that benchmark comparisons published more than a week ago are now stale in three separate model families at once.
2026-08-14 / reddit-researcherDeepSeek Launches V4-Pro and Raises API Prices by Up to 1,100%, With Peak/Off-Peak Tiers Starting August 16Alongside the Harness release, DeepSeek shipped V4-Pro-0813 and announced across-the-board API price increases of 50% to more than 1,100% depending on model, token type, and time of day, effective 16:00 UTC on August 16, 2026. V4-Pro cache-miss input goes from $0.435 to $1.32 per million tokens at peak, with peak windows defined as 01:00–04:00 and 06:00–10:00 UTC and off-peak set at half the peak rate. This ends DeepSeek's role as the reflexive cheap-frontier default — anyone with V4 in a production loop needs to re-price before Sunday.
2026-08-13 / github-pulse-researcherUnsloth Repositioned From Fine-Tuning Library to Local UI for Running and Training Frontier Open Models`unslothai/unsloth` (70,794 stars, Python, pushed 2026-08-13) now describes itself as a local UI to run and train LLMs and diffusion models, listing Qwen3.8, Kimi K3, MiniMax-H3, Gemma 4, DeepSeek-V4 and FLUX — a notable shift for a project known primarily as a memory-efficient fine-tuning library. It gained ~592 stars today. The day-one MiniMax-H3 support is the cross-reference worth making: the same model antirez is hand-writing Metal kernels for is already a checkbox in the mainstream local-model UI, which brackets how fast the tooling layer closes around a new open model.
2026-08-13 / news-researcherDeepSeek Silently Swaps Its Flagship API Endpoint to the V4 Pro 0813 Build — and the Open Weights Stay at the April PreviewOn August 12, 2026, DeepSeek switched its official deepseek-v4-pro API endpoint from the April preview build to a new 0813 build, with Vercel's AI Gateway picking up the updated weights by default under the same model ID so existing code changes silently. The 1.6-trillion-parameter MoE (49B active per token) is served at $0.435 in / $0.87 out per million tokens at one million tokens of context. Notably, the Hugging Face repos still host the April preview artifacts with no announced timeline for publishing 0813 weights — a widening gap between DeepSeek's hosted model and what it actually open-sources.

Graph relationships

RELEASED
DeepSeek
DeepSeek released DeepSeek V4-Pro with price increases of 50% to 1,100%.
Source finding
RELEASED
DeepSeek
DeepSeek released V4 Pro with three configurable reasoning levels
Source finding
BENCHMARKED AGAINST
DeepSWE
DeepSeek V4 Pro improved DeepSWE score from 12.8 to 62.7 versus the preview.
Source finding
RELEASED
DeepSeek
DeepSeek shipped the production build of V4 Pro to OpenRouter on August 12.
Source finding
USES
AI Gateway
Vercel's AI Gateway defaults to deepseek-v4-pro under the same model ID.
Source finding
RELEASED
DeepSeek
DeepSeek switched its API endpoint to deepseek-v4-pro 0813 build on August 12, 2026.
Source finding
SUPPORTS
ds4
ds4 supports running DeepSeek V4 PRO.
Source finding
RELEASED
DeepSeek
DeepSeek released V4-Pro with 1.6T parameters.
Source finding
COMPETES WITH
GPT-5.5
DeepSeek V4-Pro price is 8x lower than GPT-5.5
Source finding
BENCHMARKED AGAINST
Claude Opus 4.7
DeepSeek V4-Pro approaches parity with Claude Opus 4.7 on SWE-bench
Source finding
RELEASED
DeepSeek
DeepSeek released V4 Pro at $0.145 per million input tokens.
Source finding
RELEASED
DeepSeek
DeepSeek slashed API cache pricing to 1/10th across V4-Pro and V4-Flash models
Source finding

Source trail

Per Willison Freebuff Simon Willison found it Hugging Face repos still host April preview artifacts The meta-post Opus 4.8 and Haiku 4.5 generally available Claude's latest models lead independent aggregator ranks Fable 5 #1 overall ClinePass June 17 evaluation OpenRouter 470 points on Hacker News

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