Quantom Economic Synthesis

Original Ask

The source document is Murat's Industry Outreach Strategy Memo (2026-05-17), which names 24 individuals across the five tire majors and four CB producers, maps the supplier dependencies, and gives Quantom a 90-day action plan against EU Battery Regulation 2023/1542 binding deadlines.

Executive Synthesis

Four independent economic models — Claude Opus 4.7, GPT-5.5 Pro, Grok Heavy, Gemini Deep Think — agree on the shape of the answer and disagree on the magnitude. The shape is unanimous; the magnitude divergence is informative and is preserved below as a modeling spread rather than averaged away.

What all four models agree on

Where the models diverge — and why it matters

The four models split into two camps on time horizon and ambition:

• Near-term realism (GPT-5.5 Pro): 2026–2032 horizon, $57M base-case EV at 25% discount / 15× EBITDA. Treats batteries as a sliver of revenue (<$2M/yr through 2032). Uses $175/tCO₂ base credit pricing. Most appropriate framing for the pre-seed conversation.
• Venture-scale upside (Opus 4.7, Grok Heavy, Gemini DT): 2026–2035 horizon. Base EVs span $467M (Opus) to ~$942M (Gemini at 8× terminal) to $1.57B (Opus probability-weighted across Bear/Base/Bull). These are the right framing for the Series A / strategic-acquirer conversation, but each carries assumption stacks worth challenging line by line.

The honest read: GPT-Pro's number is what investors will diligence; Opus/Grok/Gemini's range is what investors will dream toward. Both belong in the pitch — never the same slide.

Convergence and Divergence Across Models

Where the four independent runs agree, the answer is high-conviction. Where they diverge, the spread itself is the modeling signal.

Unanimous

Modeling spread — base-case numbers across the four models

Where the models converged (market sizing, supplier map, credit floor, FE-as-existential), the read is bankable. Where they diverged (2030 EBITDA, terminal revenue, battery sizing), the divergence is a real modeling decision — the answer depends on how you treat royalty trajectories and battery-volume timing, and reasonable people will land in different places. Both belong in front of the audience.

Scenario Range — Side-by-Side

Each model is presented at its own base case. No averaging — these are independent runs against the same source memo.

Opus 4.7 — Bear / Base / Bull / Probability-weighted

GPT-Pro — Downside / Base / Upside

Grok Heavy — Memo-uplifted single track

Grok Heavy 10-year cumulative FCF $1.62B; DCF EV at 20% WACC, 8× terminal ≈ $942M; at 12× ≈ $1.4B. Aggressive on EBITDA-margin because the model treats OpEx as a very thin line — this is the most upside-leaning of the four runs.

Gemini Deep Think — Margin-expansion lens

Gemini did not publish a year-by-year table but anchored the same narrative differently: corporate burn peaks under $4M in Years 1–2; carbon credit revenue covers OpEx entirely by Year 5; tire royalties + battery premium-material sales drop straight to bottom line; EBITDA margin expands beyond 70% by Year 5. Stated EV at 15× multiple: ~$630M (Y5), ~$1.53B (Y6). Consistent with the "asset-light IP licensor" framing for the strategic-acquirer audience.

Tire CB Market Sizing — Where the Money Is

Big-5 tire majors — CB demand, current supplier path, what still needs offset

Numbers from Opus 4.7 tire-market sheet, anchored to Murat's memo and public supplier announcements. Implied $ value of the Big-5 supply gap at $4,000/t premium pricing: ~$6.4B/yr addressable. Quantom 1% capture of that gap is ~$120M product pool + ~$20M credit pool; 5% capture is ~$600M / ~$96M.

Who Currently Supplies Tire CB — and How Much CO₂ Needs Offsetting

Today's tire carbon black supply chain is dominated by four furnace-process incumbents (Cabot, Birla, Orion, Tokai), all at ~2.5–3.0 t CO₂/t direct emissions (Scope 1+2) and ~5.7 t CO₂/t full-LCA. The new entrants — Monolith, Enviro, Pyrum, Delta, Scandinavian Enviro — collectively cover <500 kt/yr against ~10.5 MMT/yr tire demand. This is the supply-gap shape Quantom is built for.

Carbon-Credit Pricing — What Quantom Can Actually Bank

The four models converge on a tight band for base-case credit pricing. Three of four explicitly rejected the deck's old $400–1,000/tCO₂ assumption as too aggressive for the base case.

Battery Optionality — Modeled Lighter, Regulated Harder

The user explicitly asked for less depth on the battery side. Three of four models complied; Opus included a full hard-carbon revenue ramp through 2035 (reaching ~$540M/yr in the base case). The forced-consensus framing keeps battery as characterization revenue + optionality through 2030; commercial battery volume is post-Series-A and not part of the base case.

The binding regulatory backbone (EU Battery Regulation 2023/1542)

What Quantom can make for batteries (priority order)

Base-case battery characterization revenue (GPT-Pro)

This is enough to strengthen the Series A narrative without distracting from tire execution. Opus models a much steeper ramp (~$15M by 2030, ~$540M by 2035) on the hard-carbon line, which is plausible conditional on a single CATL or BYD landing — but should not be base-case for pre-seed.

EV Bridge — Where Value Actually Appears

The single most useful output across the four models is GPT-Pro's revenue-lane EV bridge. It isolates the contribution of each commercial layer to enterprise value and makes the punchline arithmetic-clear: credits + characterization + grants together produce ~$16M of incremental EV; tire JDAs + pilots alone produce ~$112M.

P&L and Free Cash Flow — Opus Base Case (illustrative)

The Opus model has the longest horizon and most complete P&L build. Read this as the "venture upside" trajectory; GPT-Pro's Base sits roughly 30–40% lower across the same lines.

FCF crosses zero in 2032. Cumulative FCF through 2035: ~$1.22B base, $4.6B bull, $(150M) bear. Tax assumed at 21% on positive EBIT. The base case crosses into positive EBITDA in 2031 and positive FCF in 2032. This is conditional on the capex assumption — if partners do not co-fund pilots, the capex line doubles and FCF positivity slips by 2–3 years.

Valuation — DCF + Exit Multiple, Both Methods

Opus Base — DCF (25% WACC, 3% terminal growth)

Opus Base — Exit multiple (12× 2035 EBITDA)

GPT-Pro — Base across three discount rates (15× terminal)

The 8× spread between GPT-Pro Base ($57M) and Opus Base ($467M) is mostly explained by horizon (7-year vs 10-year), terminal-multiple choice (15× vs 12× — but applied to very different terminal EBITDAs), and royalty/license trajectory assumptions on the commercial product line. Neither is wrong. Both are bounded by the same supply-gap and credit-price evidence.

Sensitivity — EV by Faradaic Efficiency × Credit Price

The Opus sensitivity table makes the FE bet visible. Read row 0.6 (Base) vs row 0.3 (Bear): doubling FE roughly doubles EV. Read column $200 vs column $400: doubling credit price adds 60–80% EV. FE is the bigger lever.

Note: these EV values reflect Opus base scenario with the FE and credit-price varied independently. Other assumptions (capacity ramp, royalty share, terminal multiple) are held to Base. EV does not collapse to zero anywhere in this grid because tire JDA / pilot revenue persists even at 30% FE — but the EBITDA narrative does collapse.

Critical Assumptions to Defend

The forced-consensus list of what has to be true for any of the model EVs to land. If any of these fail, the model fails — there is no recoverable path inside the same enterprise value range.

Recommended Commercial Framing

This framing is the one all four models point at. It does not require pretending early tonnes carry the company. They do not. The paid customer development does — and the credits, the characterization, and the regulatory tailwind on batteries are the supporting evidence that the customer development is going to land.

For the pitch deck

• Lead with the EV-bridge slide. Show that tire JDAs are the inflection, not the credits. The credits underwrite the conversation; the JDAs make the company.
• Lead with GPT-Pro's $57M base, not Opus's $1.57B prob-weighted. Reserve the upside range for the upside-case slide explicitly labeled as such.
• Name the seven assumptions in §Critical Assumptions explicitly, with the risk-mitigation move for each. Sophisticated investors will diligence these regardless; surfacing them builds credibility.
• Treat the 90-day plan as the financing milestone narrative. Six conversations, two conferences, one Puro dialogue, one 10L prototype — that is what the pre-seed is buying, and what the Series A diligence will check first.

For the Series A diligence binder

• Both spreadsheets — Opus and GPT-Pro — should ship as supplementary exhibits. They produce different EV bands; both are internally consistent. A reviewer who only sees one will assume the omitted view does not exist.
• The sensitivity grid (FE × credit price) belongs in the appendix. It is the single most useful chart for a CTO-level investor diligencing the technical risk.
• The supplier-by-supplier offset table belongs in the appendix. It demonstrates the addressable pool is real and named, not aggregated.

Economic Models — Downloads

Both economic-model workbooks ship alongside this synthesis. Opus has the longest horizon and most complete P&L build; GPT-Pro has the most disciplined credit-price assumption and the cleanest EV-bridge build. Together they bracket the venture-vs-realism conversation.

Embedded Individual Analyses

The four independent analyses, embedded verbatim. Open each accordion to read the full model output.