Will the best coding model at the end of 2026 be from OpenAI, Anthropic, Google, Meta, or another AI company? [ resolves 2026-12-31 (211D) ]
Which AI company will have the best coding model on Dec 31, 2026?
| market | resolves | P(YES) | vol (24h) | vol (cum) | RCG | venue id | ||
|---|---|---|---|---|---|---|---|---|
| Which AI company will have the best coding model on Dec 31, 2026 | 2026-12-31 | 57.0% | $750 | $101K | A | KXCODINGMODE…NTH | ||
| Which AI company will have the best coding model on Dec 31, 2026 | 2026-12-31 | 30.0% | $115 | $29K | A | KXCODINGMODE…PEN | ||
| Which AI company will have the best coding model on Dec 31, 2026 | 2026-12-31 | 7.0% | $34 | $9.2K | A | KXCODINGMODE…OOG | ||
| Which AI company will have the best coding model on Dec 31, 2026 | 2026-12-31 | 3.0% | $5 | $2.8K | A | KXCODINGMODE…XAI | ||
| Which AI company will have the best coding model on Dec 31, 2026 | 2026-12-31 | 2.0% | — | $1.1K | A | KXCODINGMODE…OON | ||
| Which AI company will have the best coding model on Dec 31, 2026 | 2026-12-31 | 1.0% | — | $419 | A | KXCODINGMODE…LIB | ||
| Which AI company will have the best coding model on Dec 31, 2026 | 2026-12-31 | 1.0% | — | $624 | A | KXCODINGMODE…EEP | ||
| Which AI company will have the best coding model on Dec 31, 2026 | 2026-12-31 | 1.0% | — | $126 | A | KXCODINGMODE…AID | ||
| Which AI company will have the best coding model on Dec 31, 2026 | 2026-12-31 | 1.0% | — | $405 | A | KXCODINGMODE…ZAI |
| venue | proposer | source | citation | arbitration | class | analyst notes |
|---|---|---|---|---|---|---|
| kalshi | Exchange Staff | livebench.ai | link | Kalshi Staff | Other | — |
kalshi.settlement_sources → "livebench.ai" ↗ No CM Signal wire has been published for this event yet.
CM Signal’s news-cycle scan surfaces the day’s top stories alongside the prediction markets pricing them. When a story references this event, its wire is published here and links back to this page.
AI grounded search reads embedded JSON-LD in HTML. Developers query REST. Agentic AI clients (Claude Desktop, Cursor) call MCP tools. AI crawlers index via /llms.txt. Same canonical record at every surface.
| HTML | browsers, AI grounded search, crawlers (embedded JSON-LD @type: Dataset) | https://clearmarket.fyi/events/kxcodingmodel-26dec/ |
| JSON | REST API for developers | https://api.clearmarket.fyi/v1/events/kxcodingmodel-26dec.json |
| MCP | agentic AI tool call (Claude Desktop, Cursor, Continue) | clearmarket.get_event("kxcodingmodel-26dec") |
| AGENT | AI crawler discovery index | /llms.txt |
Snapshot 2026-06-03. Venue data via Kalshi + Polymarket APIs. Editorial fields (tags, editorial_notes) are ClearMarket-drafted with AI assistance under editorial review. Derived fields (venues_covered, resolution_clarity_grade, rcg_score) computed at serve time. Full per-field map in the JSON record under field_provenance.
raw JSON record · same payload returned by REST endpoint {
"event_id": "CM-EVT-6DVT0GSF00",
"slug": "kxcodingmodel-26dec",
"question": "Will the best coding model at the end of 2026 be from OpenAI, Anthropic, Google, Meta, or another AI company?",
"category": "technology",
"tags": [
"technology",
"ai-coding-models",
"llm-benchmarks",
"2026",
"tech-competition",
"software-development"
],
"venues_covered": [
"kalshi"
],
"market_count": 9,
"cumulative_volume_usd": 144702,
"resolution_clarity_grade": "A",
"rcg_score": 84,
"rcg_caps": [],
"resolution_source": "livebench.ai",
"resolution_source_url": "https://livebench.ai/#/",
"arbitration_model": "kalshi_staff",
"proposer_model": "platform_staff",
"field_provenance": {
"question": {
"source": "clearmarket_editorial"
},
"tags": {
"source": "clearmarket_editorial",
"ai_drafted": true
},
"resolution_clarity_grade": {
"source": "derived",
"method": "rcg_v2_7factor"
},
"venues_covered": {
"source": "derived"
}
}
}