inclusionAI claims Ling-3.1-flash (560B total/~25B active parameters, claimed up to 1M-token context) is free through mid-October and then open-sourced; the weights landing on schedule with sustained local and agentic adoption confirm a substantive open long-context model, while a missed open-sourcing refutes it.

state: corroboratedheat: highuncertainty: mediumconvergesscott: mediumopen-model-release long-context-inference chinese-open-labsinclusionAI

Surfaced 2026-10-02T13:36:11Z — "Meet Ling-3.1-flash: ~560B total params, ~25B active/token, up to 1M-token context. We plan to open-source the model soon. Across work, cod — Nothing substantive since the Oct 1 corroboration: the velocity-spike firings are floor-relative artifacts over threads that have actually flatlined (0 pts/h, 10th peer percentile, periphery static at the same two LocalLLaMA threads plus one provider page), and the only new content is the hands-on author's mildly disappointing quality verdict. This is a quiet, dated wait — heat drops to low until weights land ~Oct 13 or the window is missed; the magnitude-valve reading reflects launch-week totals, not live spread.

What is this?

inclusionAI is Ant Group's open-model lab, whose Ling/Ring families have repeatedly landed as open weights through 2026 — including Ling-3.0-flash, announced July 24 and open-sourced under MIT on August 7 after a free-trial period, per the orcarouter writeup. Ling-3.1-flash is the next rung: a hybrid-reasoning MoE with 560B total / ~25B active parameters and a claimed 1M-token context, currently served via third-party APIs (Novita lists it at 256K context, so the 1M figure appears aspirational at serving time rather than substantiated). The specific promise at the heart of this case — free through mid-October, then open-sourced — rests on the case's two LocalLLaMA threads; the supplied web results don't independently confirm that promise for 3.1, though they corroborate that inclusionAI honored the identical free-then-open pattern for Ling-3.0-flash two months earlier.

Why it matters to Scott

Lands on the exact terrain Scott's Inference Field ebook already claimed — million-token context becoming a practical open-model capability rather than a closed-API marketing number — and if the mid-October open-sourcing lands (the identical free-then-open pattern inclusionAI honored for Ling-3.0-flash), he gets a locally runnable 560B/~25B-active testbed for his residence-dividend vs. bigger-retrieval-bucket distinction on the gamepc/Ollama stack. Kept at medium because the load-bearing facts are still unverified: the free-then-open promise rests on two LocalLLaMA threads and Novita serves the model at 256K, so this is a watchable test of his long-context claims, not yet a result.

ip:source.the-inference-field-ebookip:concept.residence-dividendip:concept.attention-budgetdev:concept.hardware-aware-local-inferencedev:project.gamepcradar:ling-flash-vl-releaseradar:ling-30-flash-fin-open-weightsradar:concept.open-weightsradar:concept.long-context-inferenceradar:concept.sparse-moe

queries asked of Scott's wikis

chinese labs open weights strategy
long context vs RAG knowledge systems
sparse MoE local inference economics
open release promise tracking lab credibility
agentic function calling open models
1M token context local hardware requirements

Measured heat

now 0 pts/hpeak 142 pts/hcomments 0/hpeers p0momentum: steady2 platformsage 290h

points/hour across evidence · reading as of 2026-10-12 02:59:37.977291+11:00 · deterministic, not a model opinion

How the heat travelled

09-29 14:00	⭐ origin echo-reconstructed	"Meet Ling-3.1-flash: ~560B total params, ~25B active/token, up to 1M-token context. We plan to open-source the model soon. Across work, cod Ant Ling (@AntLingAGI) — Ant Group's Ling team on x (echo) · attributed from reddit.post.1wuboum, reddit.post.1wubcbb	—
09-30 17:36	first on r/LocalLLaMA · published · +27.6h	Ling-3.1-flash: ~560B total params, ~25B active/token, up to 1M-token context- Free trail for 2 weeks then open source Muhlwa_Sholanke	—
09-30 17:36	amplified on r/LocalLLaMA 👑	reddit.post.1wubcbb Muhlwa_Sholanke	peak 188 · 55 comments · 61% of case engagement
09-30 17:49	amplified on r/LocalLLaMA	reddit.post.1wuboum Elouakili_Flexy	peak 68 · 22 comments · 23% of case engagement
10-01 09:16	amplified on r/LocalLLaMA	reddit.post.1wuuqpp jaykayenn	peak 44 · 23 comments · 17% of case engagement
09-30 18:20	our radar first saw it · +28.3h	discovery anchor: reddit.post.1wuboum	—
10-02 13:36	reached heat=high · +71.6h · via queue+ledger	—	—

pace: p81 vs 1188 stories at the 168h mark (now 290h old) — ahead of elevenlabs-v4-release (1.0x), behind sous-physics-benchmark-regrading (1.0x)

Evidence (4) — ⭐ canonical anchor

source	object	author	score	comments
🟠 reddit	Another Ling model comes out, same receipt, 2 weeks free to use, then open source. Chinese labs do contribute a lot to open source community LocalLLaMA Retrieved article excerpt Open article · Retrieved 2026-09-30T18:42:55.966360+00:00 [Inclusionai](https://vercel.com/ai-gateway/models/labs/inclusionai) # Ling 3.1 Flash Ling 3.1 Flash is InclusionAI's hybrid reasoning language model for coding, multi-step analysis, and tool-using agents. It has 560B total parameters with 25B activated parameters and supports long-context text workflows. [View API reference](https://vercel.com/ai-gateway/models/ling-3.1-flash#api) PricePrice : Free Free 24h uptime : Loading AI Gateway uptime [Get API key](https://vercel.com/d?to=%2F%5Bteam%5D%2F~%2Fai-gateway%2Fquick-start%3FshowCreateKeyModal%3Dauto%26utm_source%3Dgateway-model-page%26utm_campaign%3Dai-gateway-models&title=Get%20API%20key)[Read the docs](https://vercel.com/docs/ai-gateway) APIAPIClaude CodeClaude CodeCodexCodexHermesHermesCommand CodeCommand CodeOpenClawOpenClawfxfx AI SDK AI SDKChat CompletionsMessagesResponses AI SDKAI SDKChat CompletionsChat CompletionsMessagesMessagesResponsesResponses TypeScriptTypeScriptPythonPython ``` 1 import { streamText } from 'ai' 2 3 const result = streamText({ 4 model: 'inclusionai/ling-3.1-flash', 5 prompt: 'Why is the sky blue?' 6 }) ``` Copy for agent[Read docs](https://vercel.com/docs/ai-gateway/sdks-and-apis/ai-sdk) ## [Copy link to heading](https://vercel.com/ai-gateway/models/ling-3.1-flash#playground)Playground Try out Ling 3.1 Flash by Inclusionai. Usage is billed to your team at API rates. Free users (those who haven't made a payment) get $5 of credits every 30 days. inclusionai logoLing 3.1 Flash inclusionai logo Ling 3.1 Flash Explain quantum computing in simple termsWrite a haiku about the oceanWhat are the tradeoffs of TypeScript vs JavaScript? ## [Copy link to heading](https://vercel.com/ai-gateway/models/ling-3.1-flash#providers)Providers Route requests across multiple providers. Copy a provider slug to set your preference. Visit the [docs](https://vercel.com/docs/ai-gateway/provider-options) for more info. Using a provider means you agree to their terms, listed under Legal. Promotional pricing ends on October 13, 2026. Checking availability for your team Columns (13) \| Provider \| \| --- \| \| Context \| Max Output \| Latency \| Throughput \| Input \| Output \| Cache \| Web Search \| Capabilities \| ZDR \| No Training \| Free AI Gateway Credit \| Release Date \| \| \| --- \| --- \| --- \| --- \| --- \| --- \| --- \| --- \| --- \| --- \| --- \| --- \| --- \| --- \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| --- \| --- \| --- \| --- \| --- \| --- \| --- \| --- \| --- \| --- \| --- \| --- \| --- \| --- \| --- \| \| novita logo [Novita AI](https://vercel.com/ai-gateway/models/providers/novita) Free Legal:[Terms](https://novita.ai/legal/terms-of-service)•[Privacy](https://novita.ai/legal/privacy-policy) \| 262K \| 33K \| 2.2 s \| 91 tps \| Free \| Free \| \| — \| \| \| \| \| 09/29/2026 \| \| ## [Copy link to heading](https://vercel.com/ai-gateway/models/ling-3.1-flash#uptime)Uptime24 hours 1W 1D 1H Direct request success rate on AI Gateway and per-provider. Visit the [docs](https://vercel.com/docs/ai-gateway/models-and-providers/uptime) for more info. 1W 1D 1H ## [Copy link to heading](https://vercel.com/ai-gateway/models/ling-3.1-flash#throughput)Throughput24 hours 1W 1D P50 throughput on live AI Gateway traffic, in tokens per second (TPS). Visit the [docs](https://vercel.com/docs/ai-gateway/models-and-providers/metrics) for more info. ## [Copy link to heading](https://vercel.com/ai-gateway/models/ling-3.1-flash#latency)Latency24 hours 1W 1D P50 time to first token (TTFT) on live AI Gateway traffic, in milliseconds. View the [docs](https://vercel.com/docs/ai-gateway/models-and-providers/metrics) for more info. ## Getting started Call Ling 3.1 Flash through AI Gateway with the AI SDK `generateText` and `streamText` functions, or through the OpenAI Chat Completions, OpenAI Responses, and Anthropic Messages APIs by changing the base URL. AI Gateway authenticates the request and routes it to an available provider. Install the AI SDK (`pnpm add ai dotenv`), create an API key from the [API Keys page](https://vercel.com/d?to=%2F%5Bteam%5D%2F%7E%2Fai-gateway%2Fapi-keys&title=AI+Gateway+API+Keys), and set it as `AI_GATEWAY_API_KEY` in your environment. Full setup is covered in the [text generation quickstart](https://vercel.com/docs/ai-gateway/getting-started/text). index.ts ``` 1 import { generateText } from 'ai'; 2 import 'dotenv/config'; 3 4 async function main() { 5 const result = await generateText({ 6 model: 'inclusionai/ling-3.1-flash', 7 prompt: 'Why is the sky blue?', 8 }); 9 10 console.log(result.text); 11 } 12 13 main().catch(console.error); ``` ## Top-level parameters The same Ling 3.1 Flash request in each API format AI Gateway supports. AI SDK v7Chat CompletionsResponses APIMessages API top-level-params.ts ``` 1 import { generateText } from 'ai'; 2 import 'dotenv/config'; 3 4 async function main() { 5 const result = await generateText({ 6 model: 'inclusionai/ling-3.1-flash', 7 system: 'You are a concise technical assistant.', 8 prompt: 'Summarize the tradeoffs between static generation and SSR.', 9 maxOutputTokens: 1024, 10 }); 11 12 console.log(result.text); 13 } 14 15 main().catch(console.error); ``` Standard parameters like `prompt`, `messages`, `temperature`, and `tools` work as documented in the AI SDK docs. These are the parameters with model-specific behavior. \| Parameter \| Type \| Required \| Description \| \| --- \| --- \| --- \| --- \| \| `model` \| `string` \| Yes \| Model ID in the form `creator/model`, e.g. `inclusionai/ling-3.1-flash`. AI Gateway routes the request to an available provider. \| \| `maxOutputTokens` \| `number` \| No \| Hard cap on generated tokens. Ling 3.1 Flash supports up to `32,768` output tokens. Reasoning tokens count toward this limit. \| \| `reasoning` \| `'provider-default' \| 'none' \| 'minimal' \| 'low' \| 'medium' \| 'high' \| 'xhigh'` \| No \| Provider-agnostic reasoning effort, available in AI SDK 7 or later. Maps to the provider’s native reasoning configuration; reasoning settings under `providerOptions` take precedence when both are set. See the Reasoning section below. \| \| `providerOptions` \| `Record<string, JSONValue>` \| No \| AI Gateway routing options under `gateway`, plus any provider-native options under the provider’s own namespace — see the table below. \| ## Input limits \| Input \| Formats \| Sources \| Max count \| Max size \| Limits \| \| --- \| --- \| --- \| --- \| --- \| --- \| \| Text \| — \| — \| — \| — \| Prompt and response share the 262K-token context window \| ## Provider options Set AI Gateway routing options under `providerOptions.gateway`. For provider-specific options, pass them under the provider’s namespace as documented by the AI SDK. Learn more in the [AI SDK provider docs](https://ai-sdk.dev/providers/ai-sdk-providers). provider-options.ts ``` 1 import { generateText } from 'ai'; 2 import 'dotenv/config'; 3 4 async function main() { 5 const result = await generateText({ 6 model: 'inclusionai/ling-3.1-flash', 7 prompt: 'Why is the sky blue?', 8 providerOptions: { 9 gateway: { 10 only: ['novita'], 11 }, 12 }, 13 }); 14 15 console.log(result.text); 16 } 17 18 main().catch(console.error); ``` These AI Gateway routing options apply to every model. Provider-specific options pass through under the provider’s own namespace (for example `providerOptions.anthropic`) exactly as documented by the AI SDK. \| Parameter \| Type \| Required \| Description \| \| --- \| --- \| --- \| --- \| \| `providerOptions.gateway.only` \| `string[]` \| No \| Restrict routing to these provider slugs. Requests fail over only within the listed providers. \| \| `providerOptions.gateway.order` \| `string[]` \| No \| Preferred provider order. Listed providers are tried first; unlisted providers remain available as fallbacks. \| \| `providerOptions.gateway.sort` \| `'cost' \| 'ttft' \| 'tps'` \| No \| Rank candidate providers by price, time to first token, or tokens per second instead of the default routing order. \| \| `providerOptions.gateway.zeroDataRetention` \| `boolean` \| No \| Route only to providers with a zero-data-retention policy for this model. \| ### Routing across providers AI Gateway serves the same model through multiple providers and fails over automatically. `order` expresses a preference while keeping every provider eligible; `only` is a hard allowlist — if none of the listed providers are available the request fails instead of falling back. Options under a provider's own namespace (for example `providerOptions.anthropic`) are forwarded to that provider with the request. Providers ignore option namespaces that don't apply to them, so it is safe to set provider options alongside `gateway` routing options. ## Reasoning AI Gateway bridges reasoning across every API format. The AI SDK exposes a provider-agnostic top-level `reasoning` level (`none`, `minimal`, `low`, `medium`, `high`, or `xhigh`); the Chat Completions and Responses formats take the same effort under `reasoning.effort`; and the Anthropic Messages format uses a native `thinking` token budget. Whichever you send, the gateway maps it to the target model’s native configuration, converting between effort levels and token budgets as needed. Reasoning-related settings under `providerOptions` take full precedence over the top-level `reasoning` value and are never merged. Reasoning tokens typically count toward your output-token usage, though how they’re reported and billed varies by provider. Learn more in the [AI Gateway reasoning guide](https://vercel.com/docs/ai-gateway/models-and-providers/reasoning). AI SDK v7Chat CompletionsResponses APIMessages API reasoning.ts ``` 1 import { generateText } from 'ai'; 2 import 'dotenv/config'; 3 4 async function main() { 5 const result = await generateText({ 6 model: 'inclusionai/ling-3.1-flash', 7 prompt: 'Explain the Monty Hall problem step by step.', 8 reasoning: 'high', 9 }); 10 11 console.log(result.text); 12 } 13 14 main().catch(console.error); ``` ## Tool calling Expose tools the model can call. Define each tool’s inputs with a Zod schema. tool-calling.ts ``` 1 import { generateText, tool } from 'ai'; 2 import { z } from 'zod'; 3 import 'dotenv/config'; 4 5 async function main() { 6 const result = await generateText({ 7 model: 'inclusionai/ling-3.1-flash', 8 prompt: 'What is the weather in San Francisco?', 9 tools: { 10 getWeather: tool({ 11 description: 'Get the current weather for a location', 12 inputSchema: z.object({ location: z.string() }), 13 execute: async ({ location }) => ({ location, temperatureC: 18 }), 14 }), 15 }, 16 }); 17 18 console.log(result.text); 19 } 20 21 main().catch(console.error); ``` ## [Copy link to heading](https://vercel.com/ai-gateway/models/ling-3.1-flash#similar)More models by Inclusionai All Text Code Video Input All Use Cases Columns (13) \| Model \| \| --- \| \| Context \| Latency \| Throughput \| Input \| Output \| Cache \| Web Search \| Capabilities \| Providers \| ZDR \| No Training \| Free AI Gateway Credit \| Release Date \| \| \| --- \| --- \| --- \| --- \| --- \| --- \| --- \| --- \| --- \| --- \| --- \| --- \| --- \| --- \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| --- \| --- \| --- \| --- \| --- \| --- \| --- \| --- \| --- \| --- \| --- \| --- \| --- \| --- \| --- \| \| inclusionai logo [inclusionai/ling-3.0-flash-vl](https://vercel.com/ai-gateway/models/ling-3.0-flash-vl) \| 256K \| 1.9 s \| 229 tps \| $0.08/M \| $0.22/M \| Read$0.02/M \| — \| \| novita logo \| \| \| \| 09/08/2026 \| \| \| inclusionai logo [inclusionai/ling-3.0-flash-sante](https://vercel.com/ai-gateway/models/ling-3.0-flash-sante) \| 256K \| 0.8 s \| 186 tps \| Free \| Free \| \| — \| \| novita logo \| \| \| \| 09/04/2026 \| \| \| inclusionai logo [inclusionai/ling-3.0-flash-fin](https://vercel.com/ai-gateway/models/ling-	Elouakili_Flexy	68	22
🟠 reddit	Ling-3.1-flash: ~560B total params, ~25B active/token, up to 1M-token context- Free trail for 2 weeks then open source LocalLLaMA	Muhlwa_Sholanke	185	54
🟧 echo.x ⭐	"Meet Ling-3.1-flash: ~560B total params, ~25B active/token, up to 1M-token context. We plan to open-source the model soon. Across work, cod	Ant Ling (@AntLingAGI) — Ant Group's Ling team	—	—
🟠 reddit	12hrs with Ling 3.1 Flash LocalLLaMA	jaykayenn	40	23

Interpretation history

2026-10-02T13:36:10Z
magnitude valve eligible (multi-platform, top-decile engagement) and never alerted; deterministic escalation to deliver
2026-10-01T09:38:48Z
The case has moved from claim-only to corroborated on substance, not engagement: Vercel AI Gateway (via Novita) independently serves Ling-3.1-flash free with the promotional window pinned to a date — October 13, 2026 — and a 12-hour pre-release hands-on shows the 560B/A25B model running locally and producing a working build now. That makes the mid-October open-weights landing the case's single pending test. The launch velocity spike (peak ~142 pts/h) has fully decayed to ~2.5 pts/h with the periphery stable at two platforms, so heat prices steady watch toward the dated catalyst, not launch buzz; magnitude-valve eligibility is answered by the cooling curve, not by dismissing the spread.
2026-10-01T09:23:35Z
evidence attached: reddit.post.1wuuqpp — Early 12-hour hands-on with Ling 3.1 Flash 560B before its open-sourcing, direct pre-release local-user evidence for the watching case.
2026-09-30T19:44:59Z
origin walked (opencode/cheap-glm, conf 0.93): anchor reddit.post.1wuboum -> echo.x.a06b5f76fb by Ant Ling (@AntLingAGI) — Ant Group's Ling team
2026-09-30T19:18:22Z
grounded: converges/medium — Lands on the exact terrain Scott's Inference Field ebook already claimed — million-token context becoming a practical open-model capability rather than a closed
2026-09-30T19:09:39Z
case created — A genuinely distinct release from the open Ling-3.0-flash-VL case with a testable open-weights promise, corroborated across two LocalLLaMA threads.

Decision trace

10-10 23:34drop_targetsquiet through full ladder or over cap 8
10-07 22:35drop_targetsquiet through full ladder or over cap 8
10-02 23:36push"Meet Ling-3.1-flash: ~560B total params, ~25B active/token, up to 1M-token context. We plan to open-source the model soon. Across work, cod — Nothing substantive since the Oct 1 corroboration: t
10-02 23:36repriceNothing substantive since the Oct 1 corroboration: the velocity-spike firings are floor-relative artifacts over threads that have actually flatlined (0 pts/h, 10th peer percentile, periphery static at
10-02 23:36alert_held"Meet Ling-3.1-flash: ~560B total params, ~25B active/token, up to 1M-token context. We plan to open-source the model soon. Across work, cod — Nothing substantive since the Oct 1 corroboration: t
10-02 23:36alert_route"Meet Ling-3.1-flash: ~560B total params, ~25B active/token, up to 1M-token context. We plan to open-source the model soon. Across work, cod — Nothing substantive since the Oct 1 corroboration: t
10-02 04:22sensor_dirtyvelocity_spike
10-02 00:21sensor_dirtycomment_update
10-01 21:22sensor_dirtyvelocity_spike
10-01 19:38repriceThe case has moved from claim-only to corroborated on substance, not engagement: Vercel AI Gateway (via Novita) independently serves Ling-3.1-flash free with the promotional window pinned to a date —
10-01 19:23attachEarly 12-hour hands-on with Ling 3.1 Flash 560B before its open-sourcing, direct pre-release local-user evidence for the watching case.
10-01 19:22propose_attachEarly 12-hour hands-on with Ling 3.1 Flash 560B before its open-sourcing, direct pre-release local-user evidence for the watching case.
10-01 14:21sensor_dirtycomment_update
10-01 07:22sensor_dirtyvelocity_spike
10-01 05:44promote_anchororigin walk conf 0.93
10-01 05:18groundLands on the exact terrain Scott's Inference Field ebook already claimed — million-token context becoming a practical open-model capability rather than a closed-API marketing number — and if the
10-01 05:09createA genuinely distinct release from the open Ling-3.0-flash-VL case with a testable open-weights promise, corroborated across two LocalLLaMA threads.
10-01 04:36propose_attachHigher-spread thread (77 points, 0.94 ratio) of the same Ling-3.1-flash release just opened — corroborating community spread.