Frontier AI Research & Deployment

Advancing frontier intelligence for science, software, and enterprise.

Alchemax Labs is an artificial intelligence research and deployment organisation. We develop general-purpose foundation models, verifiable deep-reasoning systems, and sovereign infrastructure engineered for high-reliability execution.

2,000,000
Native Context Window (Alchemax-5)
89.2%
SWE-bench Verified (Alchemax-o3 Pro)
ISO / UK GDPR
Zero-Retention Sovereign Infrastructure
Evaluation Ledger · 2026.10 alchemax-o3-pro / alchemax-5

Verified Frontier Benchmarks

Standardised pass@1 evaluations across autonomous software engineering, competition mathematics, and graduate-level scientific reasoning.

SWE-bench Verified (Software Engineering) 89.2%
Industry Baseline (o1 / o3-mini): 71.7% +17.5 pts
AIME 2026 (Competition Mathematics) 96.7%
GPQA Diamond (PhD Physics, Chemistry & Biology) 88.4%
Verifiable Intelligence in Action

Built for Deep Reasoning, Synthesis & Execution

Inspect how Alchemax-o3 Pro and Alchemax-5 decompose multi-step technical problems before emitting verified outputs.

Full Model Specifications →
Task Prompt · Repository Scale (480 Files)

"Identify the memory ordering race condition in our lock-free ring buffer under weak memory models (ARM64), construct a formal litmus test, and patch the Rust implementation without introducing mutex contention."

[Alchemax-o3 Pro · Verifiable Reasoning Trace — 4.2s]
1. Scanning crates/runtime/src/ring_buffer.rs lines 114–189.
2. Detected Ordering::Relaxed load on tail_idx prior to buffer slot write; on ARMv8 this permits speculative store reordering.
3. Running internal Loom model-checker simulation: reproduced ABA hazard after 1,420avings.
4. Promoting consumer load to Ordering::Acquire and producer commit to Ordering::Release. All 4,096 Loom permutations pass.
// Verified Patch generated by Alchemax-o3 Pro
pub fn push(&self, item: T) -> Result<(), T> {
    let head = self.head.load(Ordering::Relaxed);
    let tail = self.tail.load(Ordering::Acquire); // Fixed: prevents ARM64 store reordering

    if head.wrapping_sub(tail) >= self.capacity {
        return Err(item);
    }

    unsafe {
        self.buffer[head & self.mask].get().write(MaybeUninit::new(item));
    }

    // Pairs with consumer Ordering::Acquire to guarantee slot visibility
    self.head.store(head.wrapping_add(1), Ordering::Release);
    Ok(())
}
Task Prompt · Molecular & Quantum Synthesis

"Evaluate the thermodynamic stability and binding free energy delta of candidate ligand series ALX-409 against the allosteric pocket, accounting for explicit solvent entropy."

[Alchemax-o3 Pro · Verifiable Reasoning Trace — 6.8s]
1. Encoding 3D crystallographic coordinates (PDB) + 140-page assay dataset in 2M context.
2. Computing Free Energy Perturbation (FEP) cycle across 12 substituent variants.
3. Identifying displaced high-energy water triad in sub-pocket B; fluoromethyl substitution yields -3.8 kcal/mol favourable enthalpy gain.
Candidate Series Ranking (Verified ΔΔG_bind):
─────────────────────────────────────────────────────────────
1. ALX-409-F3 (Trifluoromethyl)   ΔG = -11.4 kcal/mol  [Kd: 4.2 nM]
2. ALX-409-Cl (Chloro-aryl)       ΔG =  -9.8 kcal/mol  [Kd: 61.0 nM]
3. ALX-409-H  (Baseline Scaffold) ΔG =  -7.6 kcal/mol  [Kd: 2.6 μM]

Selectivity Index vs Off-Target Kinase Panel: >450x
Recommended Synthesis Route: 3-step Buchwald-Hartwig coupling (Yield est. 84%)
Task Prompt · Aegis Multi-Agent Execution

"Cross-examine all 1,840 supplier contracts in the Q3 acquisition dataroom against our updated UK GDPR and DORA resilience clauses, flag non-compliant indemnities, and draft redline addenda."

[Alchemax-5 + Aegis Runtime — 1,620,000 Tokens Processed]
1. Ingested 1,840 PDFs & DOCX agreements into single 2M context window.
2. Identified 27 contracts missing 24-hour incident notification SLAs under DORA Art. 19.
3. Generated clause-by-clause redlines with exact page/paragraph citations and exported audit bundle.
{
  "audit_id": "ALX-AUDIT-2026-8841",
  "documents_analyzed": 1840,
  "total_tokens": 1624910,
  "compliant_contracts": 1813,
  "remediation_required": 27,
  "critical_findings": [
    {
      "vendor": "Meridian Cloud Services Ltd",
      "clause_ref": "Section 14.2 (Page 31)",
      "issue": "Sub-processor notification window is 30 days (Policy requires <=72h)",
      "redline_status": "Addendum Drafted & Ready for Counsel Approval"
    }
  ]
}
Quantitative Evaluation

How Alchemax Compares to the Industry

Standardised zero-shot and pass@1 evaluations across reasoning, software engineering, mathematics, and long-context recall.

Read Technical Reports →
Benchmark / Capability Alchemax-o3 Pro Alchemax-5 OpenAI o1 / GPT-4.5 Claude 3.7 Sonnet
SWE-bench Verified Autonomous real-world GitHub issue resolution 89.2% 81.6% 71.7% 70.3%
GPQA Diamond PhD-level physics, chemistry & molecular biology 88.4% 84.1% 78.0% 75.2%
AIME 2026 National Olympiad qualifier competition mathematics 96.7% 88.0% 83.3% 74.0%
MMLU-Pro 10-choice graduate reasoning across 14 disciplines 96.8% 96.4% 90.8% 89.5%
Native Context Window & Recall Multi-needle retrieval @ full context length 1M Tokens (99.6%) 2M Tokens (99.8%) 128K–200K Tokens 200K Tokens

Ready to build with Alchemax Labs?

Speak with our engineering and enterprise teams about API access, custom fine-tuning, or dedicated sovereign clusters.