November 2026 New AI Models Guide: OpenAI GPT-6 Cyber, Gemini Omni 1.2 Flash, GPT-Image-2.6, Kimi K3.1 Pro & Meta Muse Ember Explained

Verdict: Beyond the flagship reasoning launches of Claude Fable 5.2 (November 9) and Gemini 4 Carbon (November 10), the first 10 days of November 2026 delivered five specialized AI model releases across security, video generation, image editing, open-weight Mixture-of-Experts, and high-volume agent routing: OpenAI’s Daybreak-restricted gpt-6-cyber (November 5), Google DeepMind’s 15-second native video generator gemini-omni-1.2-flash (November 5), OpenAI’s SVG/GIF-capable gpt-image-2.6-sunburst and gpt-image-2.6-flare (November 4), Moonshot AI’s 2.8-trillion-parameter open-weight Kimi K3.1 Pro (November 4–5), and Meta’s lightweight 1M-context agent model Muse Ember (meta/muse-ember-1.0, November 9). Developers must also prepare for mandatory Gemini API model routing deadlines taking effect between December 1 and December 3, 2026.

If you tracked our October 2026 AI models and tools release tracker, the biggest shift in early November 2026 is specialization. Rather than shipping a single monolithic chatbot for every prompt, major labs are splitting their model catalogs into domain-specific engines: verification-gated models for vulnerability discovery and life sciences, native video and vector/GIF image models, multi-trillion-parameter sparse open-weight checkpoints, and $0.10-per-million-token worker models built to execute thousands of subagent tool calls per hour.

Below is the complete, source-verified breakdown of every major AI model and API update released between late October and November 11, 2026, including exact model IDs, input versus output token limits, API pricing tiers, and deprecation schedules.

Master Summary Table: November 1–11, 2026 AI Model Releases (Plus Late-October Context)

1. OpenAI GPT-6 Cyber (gpt-6-cyber, Released November 5, 2026) & GPT-6.1 Terra

Per OpenAI’s API Changelog and the GPT-6-Cyber model specification, OpenAI launched gpt-6-cyber on November 5, 2026 specifically for authorized security teams to investigate software vulnerabilities, reproduce exploits inside isolated test environments, and verify code patches.

• Verification Gate (Daybreak Red): Standard OpenAI API accounts cannot call gpt-6-cyber. Your organization must apply for and receive Daybreak Red approval through its OpenAI account team before sending requests. This mirrors OpenAI’s October 30, 2026 rollout of gpt-6-rosalind (gpt-rosalind-research), which gates biological reasoning behind the Rosalind Research trusted-access program, as well as Anthropic’s Cyber/Life Sciences Verification Programs for claude-mythos-5-2 and Google DeepMind’s Fairwind Program for Gemini 4 Carbon for cyber.
• Context Limits & Supported Endpoints: gpt-6-cyber supports a 1,050,000-token total context window (922,000 maximum input tokens and 128,000 maximum output tokens) with text and image inputs and reasoning token support. It runs on v1/chat/completions and v1/responses (where it supports hosted_shell, apply_patch, code_interpreter, computer_use, mcp, web_search, and file_search), but does not support the Batch API (v1/batch) or fine-tuning.
• Token Pricing: For standard requests up to 272K input tokens, gpt-6-cyber costs $20.00 per 1M input tokens, $2.00 per 1M cached input tokens, $25.00 per 1M tokens for 30-minute cache writes ($50.00 for 12-hour cache writes), and $100.00 per 1M output tokens. For requests exceeding 272K input tokens, rates increase to $40.00 per 1M input tokens, $4.00 per 1M cached input tokens, and $150.00 per 1M output tokens.
• Everyday Counterpart — GPT-6.1 Terra (gpt-6.1-terra): For non-security production workloads—such as matching product photos to catalog entries, reading technical schematics, driving computer-use UI agents, and drafting text—OpenAI released gpt-6.1-terra on October 26, 2026. It shares the same 1,050,000-token context window (922K max input / 128K max output) and configurable reasoning.effort (none, low, medium, high, xhigh, max), but costs just $1.00 per 1M input tokens and $5.00 per 1M output tokens ($\le$ 272K input; $0.05 cached input)—50% less than gpt-6.1-sol ($2.00/$10.00). Note that audio and video inputs are not supported on gpt-6.1-terra, and tool calling requires the v1/responses endpoint.

2. Google Gemini Omni 1.2 Flash (gemini-omni-1.2-flash, GA November 5, 2026)

On November 5, 2026, Google DeepMind announced the general availability of Gemini Omni 1.2 Flash (gemini-omni-1.2-flash), upgrading its native multimodal video-and-audio generation engine while cutting video output token prices by 30% compared with Gemini Omni 1.1 Flash.

• 15-Second Native Clips & 30-Second Multi-Turn Extensions: Per the Gemini API release notes, gemini-omni-1.2-flash generates native video clips with synchronized audio up to 15 seconds long in a single pass. It also supports 3-to-10-second first-and-last-frame interpolation and 3-to-10-second per-turn conversational video extensions up to 30 seconds of total video length, while maintaining character, lip-sync, and camera-motion consistency across up to 6 reference images. All generated videos include an imperceptible SynthID watermark.
• Exact Video Token Math & Per-Second Cost: According to Google’s Gemini Developer API pricing specification, gemini-omni-1.2-flash is available on the Paid API tier at $1.50 per 1M input tokens (text, image, or video), $9.00 per 1M text output tokens (including thinking tokens), and $12.00 per 1M video output tokens (down from $17.50/1M on Omni 1.1 Flash). Because Google bills 720p video output at a fixed rate of 5,792 tokens per second of video, the effective Standard API cost works out to:
  • 720p video (5,792 tokens/second): ~$0.07 per second (~$0.70 for a 10-second clip; ~$1.04 for a 15-second clip).
  • 360p video (1,931 tokens/second): ~$0.023 per second.
  • 1080p video with upsampling (8,688 tokens/second): ~$0.104 per second.
  • 4K video with upsampling (17,376 tokens/second): ~$0.209 per second.
• App Availability & Automatic Routing Deadline: Beyond the Gemini API and Google Cloud (where Provisioned Throughput is now supported), Gemini Omni 1.2 Flash is live in Flow, Google Ads, Google Vids (where users with a Google account or Google Workspace subscription can generate 15-second clips at no extra charge), and the Gemini app for Google AI Ultra subscribers. Effective December 3, 2026, all API calls to gemini-omni-1.1-flash will automatically route to gemini-omni-1.2-flash and be billed at the lower 1.2 Flash rate.

3. OpenAI GPT-Image-2.6 Sunburst & Flare (Released November 4, 2026)

For visual design workflows—building on the lineup covered in our GPT Image 2.5 vs Midjourney v7 vs Ideogram 4.5 comparison—OpenAI released two new image generation and editing models on November 4, 2026: gpt-image-2.6-sunburst and gpt-image-2.6-flare.

• New Capabilities in 2.6: Available via v1/images/generations and v1/images/edits, the 2.6 generation adds adjustable complexity settings, markup-guided visual editing (also backported to supported GPT-Image-2.5 models), scalable vector graphics (SVG) generation, and animated GIF generation.
• Sunburst vs. Flare Positioning & Token Pricing: OpenAI positions gpt-image-2.6-sunburst for high-detail compositions and complex multi-element edits, while gpt-image-2.6-flare is tuned for lower-latency interactive iteration. Both models carry the same per-million-token pricing table:
  • Text tokens: $5.00 per 1M input tokens ($1.25 per 1M cached input).
  • Image tokens: $8.00 per 1M input tokens ($2.00 per 1M cached input) and $30.00 per 1M image output tokens.

4. Moonshot AI Kimi K3.1 Pro (moonshotai/Kimi-K3.1-Pro, Released November 4–5, 2026)

In the open-weight ecosystem, Moonshot AI published the weights and model card for Kimi K3.1 Pro on Hugging Face and NVIDIA NIM on November 4, 2026, followed by managed enterprise deployments on Microsoft Foundry and Amazon Bedrock (as Kimi K3.1 Pro Highspeed) on November 5, 2026.

• 2.8T-Parameter Mixture-of-Experts Architecture with Gated DSA: Per Moonshot AI’s official Hugging Face model summary, Kimi K3.1 Pro is a 93-layer Mixture-of-Experts (MoE) transformer with 2.8 trillion total parameters and 104 billion activated parameters per token (896 routed experts with 16 selected per token plus 2 shared experts, 1 dense layer, 160K vocabulary, and a 401M-parameter MoonViT-V2 vision encoder). Crucially, compared with Kimi K3, Kimi K3.1 Pro replaces full-attention Gated MLA layers with 24 Gated DeepSeek Sparse Attention (Gated DSA) layers alongside 69 KDA layers (using a 32-head, 128-dimension DSA index selecting Top-K = 2048) to keep 1,048,576-token long-context inference computationally tractable. The checkpoint is trained with quantization-aware training (QAT) using MXFP4 weights and MXFP8 activations and can be served locally on multi-GPU nodes via vLLM or SGLang.
• Vendor-Reported Benchmark Scores (Evaluated at max Effort, temperature = 1.0, top-p = 0.95): In Moonshot AI’s published evaluation table (which compares Kimi K3.1 Pro against pre-November-9 baselines including Claude Fable 5.1, GPT-6 Astra, Claude Opus 5.5, DeepSeek-V4.1-Flash-1017, and GLM-5.3), Kimi K3.1 Pro posted 65.7 on Terminal-Bench 4.0 (just behind Claude Opus 5.5 at 66.4 and ahead of GPT-6 Astra at 58.2 and Fable 5.1 at 57.9), 51.7 on SWE Marathon v1.1 (ahead of Opus 5.5 at 46.3 and Fable 5.1 at 45.6), and 92.7 on BenchCAD w/ tools (tying Fable 5.1 at 92.6). However, on Terminal-Bench-Science 0.1, Kimi K3.1 Pro scored 38.1 compared with 68.1 for GPT-6 Astra and 63.3 for Claude Opus 5.5—showing that while sparse open-weight MoE models now rival proprietary flagships on repository coding and CAD scripting, proprietary models still hold a wide lead on specialized scientific reasoning.

5. Meta Muse Ember (meta/muse-ember-1.0, Released November 9, 2026)

For high-frequency, cost-sensitive agent loops—the same tier we analyzed in our Claude Haiku 5.5 vs GPT-6 Luna vs Gemini 3.8 Flash vs DeepSeek V4.1 Flash comparison—Meta released Muse Ember (meta/muse-ember-1.0) on November 9, 2026.

• Specifications & Subagent Pairing: According to Google Cloud’s Gemini Enterprise Agent Platform partner documentation, meta/muse-ember-1.0 is a Preview reasoning model built for repetitive agentic subtasks: function calling, coding subagent steps, request routing, structured extraction, and long-document parsing. On Google Cloud’s global endpoint (/locations/global/publishers/meta/v1/responses), it supports text and image inputs with a 1,048,576 maximum input token limit and a 524,288 maximum output token limit (Batch predictions and Provisioned Throughput are not supported in Preview). Meta recommends pairing Muse Ember with larger planners like Muse Wonder or Muse Spark 1.3.
• Pricing & Routing Restrictions: On OpenAI-compatible API routers and the Meta Model API, Muse Ember is priced at $0.10 per 1M input tokens and $0.50 per 1M output tokens—matching the sub-100K prompt rate of claude-haiku-5-5 and gpt-6-luna. Developers operating under strict European data-residency rules should note that OpenRouter currently flags meta/muse-ember as unavailable for EU in-region routing.

6. Additional Early-November API Updates & December 2026 Deprecation Deadlines

Engineering teams maintaining production AI integrations should also audit their codebases for these platform updates rolled out between November 2 and November 6, 2026:

• OpenAI Live API Outbound SIP Calling (November 2, 2026): Outbound SIP phone calling via gpt-live-1 on v1/live/sessions is now generally available to all organizations, allowing voice agents to place outbound telephone calls through a configured SIP trunk provider.
• Anthropic Message Threads Beta (November 2, 2026) & Enterprise Security Controls (November 5, 2026): Anthropic launched server-side message threads in beta (via header message-threads-2026-08-12, expiring 5 minutes after the last request and deleted within 1 hour) to reduce payload size and time-to-first-token in long agent loops, alongside beta IP allowlisting (up to 1,000 IPv4/IPv6 CIDR ranges) and Security Posture compliance endpoints on November 5.
• Google Gemini 3.8 TTS Voice Remixing (November 4, 2026) & Legacy Office/Multimodal Tool Responses (November 5, 2026): Developers can now call POST /v1beta/voices with gemini-3.8-flash-tts to remix existing or designed voices via natural-language prompts, and Gemini API tool/function responses now accept audio, video, and legacy Office/OpenDocument files (DOC, PPT, ODP, ODS).
• Mandatory Gemini Model Routing Deadlines (November 6 – December 3, 2026):
  • Effective November 6, 2026: gemini-embedding-2-preview is deprecated and automatically routes to gemini-embedding-2 (identical embedding space; no vector re-indexing required).
  • Effective December 1, 2026: Both gemini-2.5-pro and gemini-2.5-flash (deprecated November 2, 2026 and removed from the AI Studio selector) will automatically reroute: gemini-2.5-pro routes to gemini-3.8-flash, and gemini-2.5-flash routes to gemini-3.5-flash-lite. Because Gemini 3.x models enforce thought_signature validation on function calls, replace thinking_budget with thinking_level, and reject legacy sampling parameters and prefilled model turns, teams must update their request schemas before December 1 to prevent breaking API errors.
  • Effective December 3, 2026: All requests to gemini-omni-1.1-flash automatically route to gemini-omni-1.2-flash.