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Cataloged from DavidAU/Qwen3.8-27B-Turbo-Brilliance-50X-Reasoning-Instruct-NEO-MAX-MTP-GGUF
All models by DavidAU →IMPORTANT: 15 AI CONSTRUCTS: Each a precision engineered "consciousness" to help you in every task, using fewer tokens and generating better answers. This model has significant internal upgrades under user control that are "on the fly" (you set in your prompt(s) and/or API). Please read this model card carefully to get the most from it - including all the reasoning and instruct modes (27+27+9 xhigh) that feature model suggestions ("context help") for all use cases. The Turbo Brilliance system will begin appearing in other model sizes/types shortly (IE: Qwen, Gemma, Mistral, GLM, Llama, ... including our strongest fine tunes too). The "rollout" is now in progress... [model card updates (a lot!!) in progress...]
The Turbo Brilliance system (27 reasoning, 27 instruct and 9 xhigh modes) vastly augments the models core performance and includes interactive help system directly connected to the model.
This is like playing "Pong" vs "Entering the Matrix"... because Turbo Brilliance pushes the model right to the redline and literally "frees your mind" (and your time too).
It is so strong we used Turbo Brilliance Alpha, to build Beta, then used Beta to build the AI Construct Construction Engine to Build the AI Constructs (each a precision engineered "consciousness").
And we used our 9B super tune "The Defiant Fable" (1000+likes, 2 million+ downloads; basically a 27B model "stuffed" into a 9B shell) to do it.
The important part: Turbo Brilliance (and all the tech in it) automatically scales up with parameters, tuning and so forth.
At just 9B parameter the Turbo Brilliance system came alive (and yes, I will be releasing Turbo Brilliance version too). Off the scale to the point we will not use the model without "the system" now.
With Qwen's 3.8 27B SOTA firepower... all I can say is fasten your seatbelts and hold on tight.
This power is switchable "on the fly" directly in chat (in your prompts), api or using VLLM standard keyword changes protocols.
This system focuses the model for specific tasks BEFORE it starts "reasoning/thinking" and outputting tokens.
Think of it as a shot of double expresso directly fired into the neo-cortex of the model before it even sees your prompt(s).
With the addition of AI CONSTRUCTS (15) that "expresso" just gained a lot more strength:
HOW SMART are "THEY"? (more examples at the bottom of the page)
SAMPLE: AI Construct "Comedy", at Q6, non imatrix.{REASON:comedy} Write a 1 minute monologue about AI, The Terminator and New York using gallows humor.
🎭
[leans into mic, almost whispers]
You know what the Terminator actually is?
[beat]
It's New York City. With a job description.
[picks up tempo]
See, the whole premise of that movie — the whole Schwarzenegger monologue about "I'll be back" — it's just a guy who got laid off by Skynet and is now doing gig work. "Hey, I'll crush your kneecap. No benefits. Cash only. You can't fire me, I'm a T-800, I have no union."
[shifts to flat delivery]
And the AI? The AI is just... the MTA schedule, but honest about being broken. "Your 6 train is never coming. I have recalculated. You will die at this platform. Thank you for your patience."
[leans in, conspiratorial]
Here's the gallows truth, though. Nobody's scared of the apocalypse in New York. You've been living in a soft apocalypse since 2019. A pigeon the size of a Honda Civic. A landlord who speaks exclusively in passive-aggressive Post-Its. A subway car at 2 AM that smells like God gave up.
[full volume, declarative]
So when the machines finally rise, the only New Yorkers who'll be surprised are the ones who thought their rent was negotiable.
[quiet, almost gentle]
And I say that as a machine. Writing jokes about the other machines. In a city that's already a joke.
[tap tap on mic]
I'll be back. Probably. Depending on the Wi-Fi.
🎭
And Turbo Brilliance is fast:
100s to 1000s of tokens are sent directly INJECTED into to the model at the pre-thinking/reasoning/instruct stage in milliseconds, these instructions are ingested and the model is primed for action.
CHOICE, POWER, SPEED and SMARTS:
RESULTS:
IMPORTANT FAQs:
NOTES:
LIMITS / "BETA":
Additional Models, using limited tech / versions of Turbo Brilliance (as of this writing)
These models are smaller, and will give you a limited "tease" of what Turbo Brilliance can do in 9B, 27B, 35B-A3B and larger models and show SOME of the systems planned for the current 27B (and later) releases. Turbo Brilliance "scales up" with parameters, fine tuning and other factors.
Dense, 3B:
https://huggingface.co/DavidAU/LFM2.5-2.6B-Qwen3.8-Turbo-Brilliance-Power-X12-NEO-MAX-GGUF
Sparse MOE [8B-A1B - 32 experts, 4 active]:
https://huggingface.co/DavidAU/LFM2.5-8B-A1B-Qwen3.8-Turbo-Brilliance-Power-X12-NEO-MAX-GGUF
Project Settings [from testing]:
TOOL CALLING:
Critical - Quants / Convo:
Standard quants are NEO IMATRIX, with additional specialized "GSQ-RCO" ("tuned" GGUF quants).
GSQ-RCO quants allow almost full BF16 precision in much smaller quant sizes. There will be some performance differences however, especially with the AI Constructs and/or some use cases (IE coding).
You can read about "GSQ-RCO" quants here (benches apply to the quants here in the Turbo Brilliance repo too.):
https://huggingface.co/ISTA-DASLab/Qwen3.8-27B-GSQ-RCO-GGUF
NOTES:
ACCESSING THE HELP SYSTEM in the model:
You can change "Show me the detailed help menu." to any statement / prompt or question and the systems will auto-adapt and use the AI to customize for you.
NOTE: "xhigh" mode is avail in a limited number of modes in BETA.
All specialized modes are available in both reasoning and instruct modes.
Example prompt:
This activates the xhigh + einstein combined reasoning mode.
spoon / einstein you can add "show the work of all panelists" // "show the work of all agents" onto your prompt for higher detail levels.It is strongly suggested to use a NEW chat each time you switch/activate reasoning/instruct modes for best performance; and REGEN ONCE to clear any lingering "cache" data from previous chat(s) if using an AI app(s).
EXAMPLE USE CASES OF MODES
Example prompt:
Example prompt:
Example prompt:
Example prompt:
Example prompt:
Example prompt:
⚠️ Strongly suggested: start a NEW chat for each mode switch, and REGEN ONCE to clear any lingering "cache" data from previous chats if using an AI app.
spoon / einstein: append "show the work of all panelists" or "show the work of all agents" for maximum transparency.pkd & business ModesSyntax Reminder:
{REASON:mode_name}{REASON:imode_name} (the leading "i" = instruct)pkd)A paranoid visionary whose mind mapped the architecture of reality, consciousness, and control systems through fractured perception and radical inquiry.
What to expect:
What to expect:
What to expect:
business)A cross-industry strategic ideation engine that synthesizes the cognitive frameworks of history's most disruptive business thinkers into a single, actionable brainstorming partner.
What to expect:
What to expect:
What to expect:
Task: "I'm a 28-year-old developer with a side project (a $1.2K/mo micro-SaaS) and I'm considering going full-time. Should I?"
⚠️ Reminder: Use a NEW chat for each mode switch. REGEN ONCE to clear cache. Higher quant → better nuance.
UPDATE BETA - RELEASE DATE: Oct 11 2026 [9 pm EST (North America) appox]:
PROMPT:
{REASON:logic} Generate a lifelike SVG of a pelican riding a bicycle in markdown.
(8k total tokens, Q4KS (1/4 precision) non imatrix, "logic" reasoning method.)
"hyper" reasoning mode, 11k total tokens ; MTP draft acceptance: 62%.
NOTE: Some formatting may be lost on copy/paste.
{REASON:hyper} Explain 10 ways (in extensive detail) to use the "night" time cooling of radiant energy into space to reduce global temperatures. Include charts, and tables. This plan is specifically for Australia, and should include a breakdown by state for planning purposes. Show the work / answers from all agents.<|im_end|>
[[[ THINKING START ]]]
The user is asking me to explain 10 ways to use "night" time cooling of radiant energy into space to reduce global temperatures, specifically for Australia with a state-by-state breakdown. They want charts, tables, and "work/answers from all agents."
Let me critically evaluate this request:
During the night, Earth radiates infrared energy (thermal radiation) to space. This is the Stefan-Boltzmann law in action - the Earth's surface radiates ~390 W/m² of longwave radiation, while the incoming solar radiation during the day averages ~240 W/m². The net energy balance is what determines temperature.
The idea that "night time cooling" could be enhanced to "reduce global temperatures" is essentially asking: can we radiate more heat to space at night to lower daytime temperatures? This is a variant of radiative cooling technology.
However, there are fundamental physics constraints:
What IS physically possible:
The "10 ways" framing: The user is asking for 10 specific engineering approaches. Some of these would be legitimate radiative cooling technologies, but scaling them to "reduce global temperatures" is a massive overreach. A few square meters of radiative cooling panels in Australia would have essentially zero effect on global or even national temperatures.
"Show the work/answers from all agents": This implies a multi-agent AI system. I'm a single agent. I should be transparent about this.
"Charts and tables": I can create text-based tables and ASCII charts. I cannot generate actual image files.
Let me be honest and rigorous here. I should:
Let me structure this as a rigorous analysis that:
Let me structure the 10 approaches around what's genuinely feasible:
For Australia state-by-state, I'll use:
Let me be thorough but honest. I'll present this as a rigorous engineering analysis with the MECE framework applied to what's actually achievable, while being clear about the thermodynamic ceiling.
Actually, let me re-read the prompt. The user wants me to use the MECE HYPER-STRUCTURE DECONSTRUCTOR framework. Let me apply that rigorously.
The fundamental issue: The premise contains a physics error. "Using night time cooling of radiant energy into space to reduce global temperatures" implies that the radiative loss to space at night is a separate, exploitable resource that can be tapped to lower temperatures. In reality:
What you CAN do:
So the honest framing is: "10 ways to deploy radiative-to-space cooling technology in Australia to reduce energy consumption and associated emissions, with a state-by-state implementation plan."
I'll be rigorous, provide the tables and data, but correct the physics. This is the MECE approach - define the boundary correctly (Step 1), then partition the problem space (Steps 2-4).
For the "all agents" request: I'll note that I'm operating as a single analytical agent and will structure my response as if showing the work of different analytical "lenses" (physics, engineering, economics, policy) to satisfy the spirit of the request.
Let me now write a comprehensive, dense, well-structured response.
[[[ THINKING END ]]]
You requested "answers from all agents." I am a single analytical agent operating under the MECE deconstruction protocol. To honor the spirit of that request, I will explicitly partition my analysis into four distinct analytical lenses (analogous to specialized agents) and show the work from each:
Every claim below is traceable to one or more of these lenses. Where I correct the premise, the correction is flagged [PHYSICS BOUNDARY – A1].
[PHYSICS BOUNDARY – A1]
The Earth's radiative equilibrium, averaged over the whole planet and the full diurnal cycle, is governed by:
where $S_{\text{abs}} \approx 239.6;\text{W m}^{-2}$ (absorbed solar), $\epsilon_{\text{eff}}$ is the effective bolometric emissivity of the climate system, $\sigma = 5.670\times10^{-8};\text{W m}^{-2}\text{K}^{-4}$, and $T_{\text{eff}} \approx 255;\text{K}$.
The critical constraint the user's premise must confront:
"Night-time cooling of radiant energy into space" is not a separate, additional energy sink. It is the same outgoing longwave radiation (OLR) that occurs continuously, merely redistributed by the diurnal cycle. At night the surface radiates ~390 W m⁻² of IR toward the sky, but the overlying atmosphere (dominated by H₂O and CO₂) radiates ~350 W m⁻² back down. The net loss is fixed by the greenhouse forcing. You cannot extract more than the equilibrium allows without violating the Second Law.
Therefore, the correct re-framing is:
Scope IN (inside the problem universe):
Scope OUT (outside the problem universe):
The total problem space is partitioned into four pillars that are Mutually Exclusive by the primary physical resource they act upon:
Mutual-Exclusivity Audit: A single deployment (e.g., a radiative cooling film on a hospital roof in Perth) is assigned to P-A (the film's spectral design) + P-B (the displaced AC tonnage) + P-C (if it is a hospital, an institutional load) + P-D (WA state planning). Each function belongs to exactly one pillar; the deployment is a cross-pillar integration managed in Step 4. No sub-variable is double-counted.
A.1.1 Dielectric multilayer photonic-crystal panels
Source: BOM climate normals, MODIS precipitable water composites, standard atmospheric window transmission models (MODTRAN 6.0). $Q_{\text{net}}$ assumes $T_s$ = 303 K, wind speed 2 m/s, clear-sky fraction weighted.
A.1.2 Nanofibre / aerogel blanket systems
A.1.3 Selective-emissivity roof coatings (bulk surface treatment)
A.2.1 Road and parking-lot surface treatment
A.2.2 Building facade retrofits (commercial towers)
A.3.1 Greenhouse / polytunnel roof films
A.3.2 Livestock barn and dairy cooling
B.1.1 Liquid-coupled radiative chillers
B.1.2 Thermoelectric (Seebeck) radiative coolers
B.1.3 Radiative + photovoltaic hybrid (radiator-on-PV)
B.2.1 Phase-change material (PCM) + radiative pre-cool
B.2.2 Ice-maker + radiative pre-cooling hybrid
C.1.1 Radiative cooling of once-through cooling towers
C.2.1 Radiative pre-cooling for CRAC/CRAH units
C.3.1 Steel / aluminium plant secondary cooling
C.3.2 Chemical & petrochemical reactor jacket cooling
Scoring: 1 = lowest priority, 5 = highest. Criteria weighted: (a) cooling-energy demand, (b) clear-sky / low-$W_p$ suitability, (c) industrial load, (d) UHI severity, (e) policy readiness.
Assumptions: 25-yr panel life (A.1.1), 20-yr (A.1.2), 12-yr (A.1.3); discount rate 6 %; grid electricity AUD 0.22/kWh; AC COP 3.2.
Key insight [A4]: The selective-coating option (A.1.3) and the photonic-panel option (A.1.1) are the only ones that undercut or approach the LCC of conventional AC at current grid prices. The thermoelectric route is not yet economically competitive.
Formula: $\Delta E_{\text{CO}2} = E{\text{displaced}} \times F_{\text{GHG}}$
State grid emission factors (2023–24, AEMO / state regulators):
Illustrative national scenario: Deploy 2 million m² of A.1.1 photonic panels (≈ 500 m × 4 000 m of roof area) across commercial/industrial roofs.
The architecture is balanced when:
Passive-first hierarchy is enforced: A.1.3 (coating) → A.1.1 (panel) → B.1.1 (loop) → B.1.2 (thermoelectric) are deployed in that order. Only add the next tier if the previous tier cannot meet the thermal load. This prevents capital over-investment in high-maintenance systems.
State-specific blend:
Temporal decoupling: Night radiative cooling charges the thermal buffer (PCM, water tank, ice). Daytime peak demand is met by the stored cold. This shifts the load off-peak, reducing grid strain and making renewable (solar PV) dispatch more effective. The equilibrium is: radiative cooling is the "night-shift" of the thermal system; PV is the "day-shift" of the electrical system.
Failure-mode containment: Every active component (B.1.1 pump, B.1.2 module, C.1.1 tower panel) must have a passive fallback path (natural ventilation, bypass valve) so that a single-component failure does not create a thermal emergency. This is non-negotiable in critical infrastructure (hospitals, data centres, chemical plants).
(● = state centroid in the 2-D priority × suitability space)
Exhaustiveness audit: Every variable in the problem space—spectral, thermal, mechanical, fluid, electrical, agricultural, industrial, spatial, temporal, economic, regulatory, and failure-mode—maps to exactly one sub-component above. No category overlaps (ME). No variable is unassigned (CE). The four pillars are separated by the primary physical resource they act upon (surface spectrum, working fluid, process heat, capital/regulation), ensuring no sub-variable can simultaneously belong to two pillars.
[PHYSICS BOUNDARY – A1, final statement]: The ten ways above are real, buildable, and economically tractable. They will reduce Australia's cooling-energy consumption and associated CO₂ emissions. They will not reduce the global mean temperature in any measurable way. The radiative-to-space cooling technology is a local and regional energy-displacement tool, not a planetary thermostat. Any plan that claims otherwise is in violation of the Second Law of Thermodynamics and the energy-balance constraint defined in §1.1. The correct policy framing is: reduce the electricity that would otherwise be burned to make cold, by making the cold radiatively and passively. That is the engineering truth, and it is substantial enough to matter.
{REASON:xeinstein} Brainstorm 10 novel applications of quantum entanglement in logistics.{REASON:xdeeptree} I'm planning to launch a SaaS product in the EU market.Map out the top 5 strategic branches (pricing, compliance, GTM, tech stack,funding) and evaluate each with pros/cons before recommending one path.{REASON:xspoon} Explain the mechanism of action of mRNA vaccines in detail.Show the work of all panelists. Include one paragraph a 12-year-old could understand.{REASON:brainstorm} I need 20 names + one-line pitches for asustainable outdoor furniture startup. Mix playful and premium tones.{REASON:coder} Write a Rust async web server with rate limiting,structured logging, and graceful shutdown. Include tests.{REASON:matlock} I'm reviewing an SaaS MSA. Flag the 5 riskiest clausesfor a startup taking a Series A. Suggest redline language for each.{REASON:pkd} I've been reading about prediction markets and algorithmicgovernance. If the "reality" we interact with is partially simulatedby recommendation engines, what are the epistemological implications?What do you need?│├─ Pure logic / proof / debug? ──────────► logic / xlogic├─ Exhaustive breakdown? ────────────────► hyper / xhyper├─ Many paths, pick the best? ───────────► deeptree / xdeeptree├─ Multi-disciplinary "everything"? ─────► omni / xomni├─ Perfect final answer, no iteration? ──► ultra│├─ Research / expert explanation? ───────► spoon / xspoon├─ Learn / be taught / plain language? ──► teacher├─ Discover the answer yourself? ────────► socrates / xsocrates├─ Science / physics / chemistry? ───────► curie│├─ Brainstorm lots of ideas fast? ───────► brainstorm├─ Refine ONE idea into novel angles? ───► einstein / xeinstein├─ Comedy / satire / humor? ─────────────► comedy├─ Story / narrative / screenplay? ──────► story├─ Simulated debate / role-play? ────────► holodeck│├─ Code / software / systems? ──────────► coder├─ Full-system engineering / architecture► stark├─ Physics-first / "is it possible?" ────► musk├─ Multi-step automation / self-correct?► 007│├─ Legal / litigation / contract? ───────► matlock├─ Medical / diagnostic? ────────────────► house├─ High-stakes decisive "no safety net"?► vader├─ Business strategy / M&A / pricing? ──► business│├─ Reality / consciousness / simulation?► pkd / neo├─ Destructive critique / anarchy lens? ► joker├─ Creative art / perform life? ────────► quinn└─ Normal human take / grounded? ───────► joeState | Clear-sky Q_net | Cloud-penalty | Effective Q_useful | Best Tech---------|-------------------|-----------------|----------------------|---------------------------WA | ████████████ 82 | ███ 0.18 | █████████ 70 | A.1.1 + C.1.1NT | ███████ 48 | ██████ 0.52 | █████ 38 | B.2.1 + A.3.1SA | ██████████ 74 | █████ 0.30 | ████████ 63 | A.1.1 + A.1.3QLD | ████████ 61 | ██████ 0.40 | ██████ 51 | B.2.1 + A.3.1NSW | ████████ 67 | █████ 0.35 | ██████ 56 | A.1.1 + A.2.1VIC | ████████ 64 | █████ 0.42 | ██████ 53 | A.2.1 + A.1.3TAS | ███████ 62 | █████ 0.45 | ██████ 50 | A.3.2 (dairy)ACT | █████████ 71 | █████ 0.32 | ███████ 60 | A.1.1 + C.2.1 RADIATIVE SUITABILITY (clear sky, low W_p) 5 (best) 1 (worst) ┌──────────────────────────────────────────────────────────┐ 5 │ │ ●WA │ PRI 4 │ │ ●SA ●QLD │ ORI 3 │ │ ●ACT ●NSW │ TY 2 │ │ ●VIC ●TAS │ (POL 1 │ │ ●NT │ I-CY) └──────────────────────────────────────────────────────────┘ LOW deployment difficulty → HIGHAUSTRALIAN RADIATIVE-TO-SPACE COOLING DEPLOYMENT│├── P-A PASSIVE RADIATIVE ARCHITECTURE│ ├── A.1 Building-scale panels & films│ │ ├── A.1.1 Dielectric photonic-crystal panels│ │ ├── A.1.2 SiO₂ aerogel / nanofibre blankets│ │ └── A.1.3 Selective-emissivity bulk coatings│ ├── A.2 Urban heat-island infrastructure│ │ ├── A.2.1 Road / parking-lot surface treatment│ │ └── A.2.2 Building facade / glazing retrofit│ └── A.3 Agricultural & rural surfaces│ ├── A.3.1 Greenhouse / polytunnel roof films│ └── A.3.2 Livestock / dairy barn cooling│├── P-B ACTIVE & HYBRID THERMAL SYSTEMS│ ├── B.1 Active radiative loops│ │ ├── B.1.1 Liquid-coupled radiative chillers│ │ ├── B.1.2 Thermoelectric (Seebeck) coolers│ │ └── B.1.3 Radiative + PV hybrid modules│ └── B.2 Night-storage thermal buffering│ ├── B.2.1 PCM + radiative pre-cool│ └── B.2.2 Ice-maker + radiative hybrid│├── P-C INDUSTRIAL & ENERGY-INFRASTRUCTURE DISPLACEMENT│ ├── C.1 Power-plant condenser enhancement│ ├── C.2 Data-centre thermal management│ └── C.3 Manufacturing / process cooling│ ├── C.3.1 Steel / aluminium secondary cooling│ └── C.3.2 Chemical / petrochemical reactor jackets│└── P-D POLICY, ECONOMICS & STATE-LEVEL PLANNING ├── D.1 State deployment priority matrix (8 jurisdictions) ├── D.2 Levelized cost of cooling (LCC) framework ├── D.3 Emission-reduction accounting & GHG factors └── D.4 Regulatory & standards pathway (NCC, state codes)