Trinity v2.1.0 — Community Announce Templates

Date: 8 February 2026 Release: https://github.com/gHashTag/trinity/releases/tag/v2.1.0

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X (Twitter) — Main Post

Trinity v2.1.0 released — local autonomous multi-modal AI agent.

What it does:
- Chat + Code + Vision + Voice + Tools + Self-Reflection
- 28M ops/sec JIT NEON SIMD (15-18x speedup)
- 400 tests, 56 dev cycles, zero failures
- No cloud. No API keys. Just download and run.

macOS / Linux / Windows binaries:
https://github.com/gHashTag/trinity/releases/tag/v2.1.0

Built with Zig. Ternary math {-1, 0, +1}. 20x less memory than float32.

#LocalAI #OpenSource #Zig #TernaryComputing #AI

X (Twitter) — Thread (5 posts)

Post 1/5

We just released Trinity v2.1.0 — a fully local autonomous AI agent.

No cloud dependency. No API keys. Download, run, done.

Chat + code + vision + voice + tools + memory + self-reflection in one system.

Thread on what makes it different:

Post 2/5

The core: Ternary Vector Symbolic Architecture (VSA).

Instead of float32, we compute with {-1, 0, +1}.
- 1.58 bits per trit (vs 32 bits per float)
- 20x memory savings
- Add-only math (no multiply needed)

JIT-compiled with ARM64 NEON SIMD: 28.10 M dot products/sec.

Post 3/5

The AI stack (56 development cycles):

Layer 0: Ternary math
Layer 1: VSA engine + JIT SIMD
Layer 2: LLM inference (GGUF) + VIBEE compiler
Layer 3: Chat, code, RAG, voice, streaming, API
Layer 4: Multi-modal agents with memory + tools
Layer 5: Unified autonomous system with self-reflection

All integrated. All local.

Post 4/5

What "autonomous" means here:

1. System auto-detects what you need (vision? code? voice?)
2. Decomposes your goal into sub-goals
3. Executes with appropriate tools
4. Reviews its own output
5. Learns from mistakes (pattern detection)
6. Tracks convergence toward phi^-1 threshold

No human in the loop required.

Post 5/5

Get it:

macOS ARM64 (full suite, 4.2 MB):
https://github.com/gHashTag/trinity/releases/tag/v2.1.0

From source (any platform):
git clone https://github.com/gHashTag/trinity
cd trinity && zig build && zig build test

400/400 tests pass. Built with Zig 0.15. MIT licensed.

Star the repo if you think local AI matters.

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Telegram / Discord — Announcement

Trinity v2.1.0 Released — Unified Autonomous System

56 IMMORTAL development cycles. 400 tests. Zero failures.

WHAT'S NEW:
- Unified autonomous AI agent (8 capabilities in one system)
- Auto-detect mode: vision + voice + code + text + tools + memory + reflection + orchestration
- Self-reflection: agent reviews own output and learns from mistakes
- JIT NEON SIMD: 28.10 M ops/sec (15-18x speedup over scalar)
- 20x memory savings with ternary {-1, 0, +1} encoding

DOWNLOAD:
https://github.com/gHashTag/trinity/releases/tag/v2.1.0

Binaries available for:
- macOS ARM64 (full suite: tri, vibee, fluent, firebird — 4.2 MB)
- macOS x86_64
- Linux x86_64
- Windows x86_64

QUICK START:
curl -LO https://github.com/gHashTag/trinity/releases/download/v2.1.0/trinity-v2.0.0-aarch64-macos.tar.gz
tar xzf trinity-v2.0.0-aarch64-macos.tar.gz
./tri --help

FROM SOURCE:
git clone https://github.com/gHashTag/trinity
cd trinity
zig build        # Build
zig build test   # 400/400 tests
zig build tri    # Run

Built with Zig 0.15. No runtime dependencies. Statically linked.

DOCS: https://gHashTag.github.io/trinity/docs/research

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Reddit — r/LocalLLaMA, r/Zig, r/MachineLearning

Title

Trinity v2.1.0: Local autonomous multi-modal AI agent — ternary computing, JIT SIMD, 400 tests, no cloud

Body

We released Trinity v2.1.0, an autonomous AI agent that runs entirely locally.

**What makes it different:**

Trinity uses ternary computing ({-1, 0, +1}) instead of floating point. This gives 20x memory savings over float32 and enables JIT-compiled NEON SIMD at 28.10 million dot products per second on ARM64.

**The autonomous system:**

Given any input, the system:
1. Auto-detects which capabilities are needed (vision, voice, code, text, tools, memory, reflection)
2. Decomposes the goal into sub-goals
3. Executes using multi-modal tool integration
4. Reviews its own output with self-reflection
5. Learns patterns from successes and failures
6. Tracks phi convergence for system health

**Stack:**
- Core: Vector Symbolic Architecture (VSA) with ternary encoding
- JIT: ARM64 NEON SIMD, x86_64 support
- LLM: GGUF model loading (works with TinyLlama, Llama, etc.)
- Compiler: VIBEE (.vibee specs → Zig/Verilog code generation)
- Built with Zig 0.15, statically linked, no dependencies

**Numbers:**
- 400 tests, zero failures
- 56 consecutive development cycles (all passing)
- 28.10 M ops/sec JIT dot product
- 15-18x speedup over scalar
- 4.2 MB full binary suite (macOS ARM64)

**Download:**
https://github.com/gHashTag/trinity/releases/tag/v2.1.0

**From source:**

git clone https://github.com/gHashTag/trinity cd trinity && zig build test # 400/400

Happy to answer questions about the ternary approach or the autonomous agent architecture.

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Hacker News

Title

Show HN: Trinity v2.1.0 – Local autonomous AI agent using ternary computing (Zig)

Body

Trinity is a local-first AI system built on ternary computing ({-1, 0, +1}) using Vector Symbolic Architecture (VSA).

Key technical points:

1. Ternary encoding: 1.58 bits/trit vs 32 bits/float. 20x memory savings. Compute uses addition only (no multiplication needed for dot products in ternary).

2. JIT compilation: ARM64 NEON SIMD with SDOT instruction processes 16 int8 elements per cycle. Measured at 28.10M dot products/sec on Apple Silicon. 15-18x over scalar.

3. Autonomous agent: 8-phase pipeline — auto-detect capabilities from natural language, decompose goals, execute with tools, self-reflect, learn patterns. Tracks convergence using phi^-1 (0.618) as the health threshold.

4. VIBEE compiler: YAML-based spec format generates Zig or Verilog code. One spec → multiple targets.

5. 400 tests, 56 development cycles, all passing.

Built with Zig 0.15. Statically linked. No runtime dependencies.

Download: https://github.com/gHashTag/trinity/releases/tag/v2.1.0
Source: https://github.com/gHashTag/trinity

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Post Timing Recommendations

Platform	Best Time (UTC)	Day
X/Twitter	14:00-16:00	Tuesday or Wednesday
Reddit r/LocalLLaMA	14:00-18:00	Tuesday-Thursday
Reddit r/Zig	14:00-18:00	Any weekday
Hacker News	14:00-16:00	Tuesday or Wednesday
Telegram	Immediate	Any
Discord	Immediate	Any

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Hashtags & Keywords

X/Twitter: #LocalAI #OpenSource #Zig #TernaryComputing #AI #MachineLearning #LLM #SIMD #VSA

Reddit flairs:

• r/LocalLLaMA: "New Model/Tool"
• r/Zig: "Project"
• r/MachineLearning: "[P] Project"

SEO keywords: local AI agent, ternary computing, vector symbolic architecture, Zig programming, NEON SIMD, autonomous agent, multi-modal AI, offline AI, no-cloud AI