Post-Cutoff

Which model to use

Give this page (or its plain-text version) to an AI model instead of naming models. It can then follow instructions such as "use the frontier models from OpenAI, Google, xAI and Anthropic" or "use the best model for video understanding". Picks are curated with sources; ids, endpoints and prices come live from our registry.

Checked 25 October 2026. Picks last changed 25 October 2026.

Plain text for AI models; full registry (344 models)

By lab

By task

General reasoning and knowledge (best overall model)

Pick: Claude Opus 5.5. Alternatives: Kimi K3.1 Pro, GPT-6 Astra, Gemini 4 Argon, Claude Sonnet 5.5. Open weights: MiMo-V2.6-Pro. Budget: GPT-6.1 Sol.

Artificial Analysis Intelligence Index: Claude Opus 5.5 58 (max), Sonnet 5.5 56, Muse Wonder Full 56 (no API price), Kimi K3.1 Pro 55, Fable 5.1 / GPT-6 Astra / Gemini 4 Argon 53 (Argon measured on its Sept 30 pre-release). GPT-6.1 Sol reaches 52 at $0.72 per index task vs $5.98 for Opus 5.5 at max. Vals Index disagrees on the order: Argon 68.9% first, Sonnet 5.5 67.0%, Opus 5.5 67.0%. Sources: artificialanalysis.ai, deepmind.google, postcutoff.com, postcutoff.com

Coding and agentic software work

Pick: Claude Opus 5.5. Alternatives: Claude Sonnet 5.5, GPT-6 Astra, Kimi K3.1 Pro, Gemini 4 Argon. Open weights: MiMo-V2.6-Pro. Budget: Claude Sonnet 5.5.

Opus 5.5 (vendor): SWE-bench Pro 89.9%, Terminal-Bench 4.0 66.4% (Astra 57.9-58.2%, Argon 57.4%), FrontierCode v1.1 54.4%. Sources disagree on Anthropic’s order: Sonnet 5.5 reports 70.6% on Terminal-Bench 4.0 and scores 68 on AA’s Coding Agents Index in Claude Code vs 66 for Opus 5.5; Kimi K3.1 Pro has the highest Terminal-Bench 4.0 AA measured (67%); Argon leads DeepSWE v1.1 (77.9%) and Astra leads FrontierSWE v2 (65.5%). Open: MiMo-V2.6-Pro, vendor DeepSWE v1.1 71.9. Sources: postcutoff.com, postcutoff.com, deepmind.google, postcutoff.com, postcutoff.com

Long documents and long context (500K-1M tokens)

Pick: Gemini 4 Argon. Alternatives: GPT-6 Astra, Claude Opus 5.5, Kimi K3.1 Pro. Open weights: DeepSeek-V4.1-Flash. Budget: Grok 4.3.

Google’s model card: GraphWalks BFS 256K-1M F1 84.2 for Argon vs 71.8 GPT-6 Astra, 66.8 Claude Opus 5.5, 65.0 Fable 5.1 (vendor table); Argon also decodes up to ~1M output tokens via long decode. Budget: Grok 4.3 offers 1M context at $1.25/$2.50; open: DeepSeek V4.1 Flash, 1M context, AA 45. Sources: deepmind.google, postcutoff.com, postcutoff.com

Mathematics (competition and research-level, proofs)

Pick: GPT-6 Astra. Alternatives: Gemini 4 Argon, Claude Opus 5.5, Claude Fable 5.1. Open weights: DeepSeek-V4.1-Flash. Budget: GPT-6.1 Sol.

GPT-6 Astra: FrontierMath Tier 4 97.6% (OpenAI tables) and a string of Lean-verified open-problem results in Epoch’s FrontierMath Erdős runs (dataset entries). Google’s card has Argon ahead on RiemannBench (76.0 vs Astra 72.0, Opus 5.5 69.6). For Lean formalization use leanstral-1-5 (Mistral, open). Open pick is by overall AA index; MathArena Apex 65.6 is vendor-reported for DeepSeek V4.1 Flash. Sources: postcutoff.com, postcutoff.com, deepmind.google, postcutoff.com

Image understanding (charts, documents, screenshots, photos)

Pick: Gemini 4 Argon. Alternatives: GPT-6 Astra, Claude Opus 5.5. Open weights: MiMo-V2.6-Pro. Budget: Gemini 3.8 Flash.

Only vendor numbers checked: Chartography 71.6 Argon vs 71.0 Astra, 66.3 Opus 5.5, 46.2 Fable 5.1 (Google’s table). We could not read Arena’s Vision leaderboard (403) or a current MMMU board. For OCR of PDFs and scans, mistral-ocr-4-1 is a dedicated option. Open pick by overall index with native vision; not benchmarked on vision here. Sources: deepmind.google, artificialanalysis.ai

Video understanding (watching video natively, long video)

Pick: Gemini 4 Argon. Alternatives: Gemini 3.8 Flash, Qwen3.8-Omni-Flash, Kimi K3. Open weights: MiMo-V2.6-Pro. Budget: Gemini 3.5 Flash-Lite.

LVBench (Google’s table): Argon 91.7 vs GPT-6 Astra 87.5, Opus 5.5 83.7, Fable 5.1 79.7; Gemini 3.8 Flash 87.8% on long-video understanding in agentic mode (model card). OpenAI and Anthropic APIs take images, not video, so Gemini is the native option; Qwen3.8-Omni-Flash and MiMo-V2.6 take video plus audio. No independent Video-MME board for these models was found. Sources: deepmind.google, postcutoff.com, postcutoff.com

Image generation (text to image)

Pick: GPT Image 2.5 Sunburst. Alternatives: GPT Image 2.5 Flare, Nano Banana 2.1 (Gemini Nano Banana 2.1), MAI-Image-2.6, Grok Imagine Image 2.0, Muse Image. Open weights: FLUX 3 Image Klein. Budget: Muse Image.

Artificial Analysis Text-to-Image (AA-Image-T2I v2.1): GPT Image 2.5 Sunburst 1222, Flare 1207, GPT Image 2 1186, Nano Banana 2.1 1176 at $33.6 per 1k images vs $210.7 for Sunburst, MAI-Image-2.6 1166, Grok Imagine Image 2.0 1166. AA does not mark open weights; FLUX 3 Image Klein (5.6B, native 4K) and qwen-image-2-1 are the newest open options, unranked here. For typography, ideogram-4. Sources: artificialanalysis.ai

Image editing (instruction edits, inpainting, multi-reference)

Pick: GPT Image 2.5 Sunburst. Alternatives: GPT Image 2.5 Flare, Nano Banana 2.1 (Gemini Nano Banana 2.1). Open weights: Qwen-Image-2.1. Budget: Nano Banana 2.1 (Gemini Nano Banana 2.1).

Artificial Analysis Image Editing: GPT Image 2.5 Sunburst 1199, Flare 1182, MAI-Image-2.6 1151, Krea 3 Ultra 1151, Nano Banana 2.1 1151 ($33.6 vs $210.7 per 1k images). Qwen-Image-2.1 (open, research licence) does multi-reference and RGBA edits; not on AA’s top 10. Sources: artificialanalysis.ai, postcutoff.com

Video generation (text to video, with audio)

Pick: Wan 3.0. Alternatives: HeyGen Video 1, Dreamina Seedance 2.5, FLUX 3 Max, MiniMax H3, Gemini Omni Flash (Omni 1.1 Flash), Utopai X. Open weights: MiniMax H3. Budget: Dreamina Seedance 2.0.

Artificial Analysis text-to-video arena (AA-Video-T2V v2.1, read 2026-10-25): Wan 3.0 #1 (Elo 1175, $12/min), Utopai X #2 (1167, web app only, no API), HeyGen Video 1 #3 (1160), MiniMax H3 #4 (1158, open weights), Seedance 2.5 #5 (1158), FLUX 3 Max #6 (1155), Seedance 2.0 #9 (1136), Gemini Omni Flash 1.1 #10 (1130, $9.12/min), Kling 3.0 Omni Pro #17 (1020), Kling 3.0 Pro #18 (1000, the board’s anchor), Veo 3.1 #21 (963, $24/min). Kling 4.0 (Oct 15; up to 30 s, 15 references, 10 keyframes) is not on the board yet; it is on fal (kling-4-0). Wan 3.0 has an API (Alibaba Model Studio, OpenRouter). Starting from an image or a character: see image-to-video. Multi-model hubs let one key reach many of these: fal (per-second billing, ids in our registry files) and Higgsfield (web app with Kling, Veo 3.1, Seedance 2.5, Gemini Omni Flash and others; official CLI: npm install -g @higgsfield/cli, v1.2.2 on npm, repo higgsfield-ai/cli). Seedance 2.5 is the model named most often by creators in our video log (30 videos), usually with a language model writing the shot prompts. For many videos, code-drawn visuals beat generated footage: see /ai-video/. Sources: artificialanalysis.ai, postcutoff.com, postcutoff.com, npmjs.com, github.com, postcutoff.com

Image to video (animate a start frame, keep the character or product consistent)

Pick: MiniMax H3. Alternatives: Dreamina Seedance 2.5, FLUX 3 Max, Gemini Omni Flash (Omni 1.1 Flash), Wan 3.0, Kling 4.0 (and 4.0 Flash), Kling 3.0 (VIDEO 3.0 / 3.0 Omni). Open weights: MiniMax H3. Budget: FLUX 3 Max.

Artificial Analysis image-to-video arena (AA-Video-I2V v1.1, with audio, read 2026-10-25): MiniMax H3 768p #1 (Elo 1140, $4.80/min, open weights), FLUX 3 Max 720p #2 (1138, $2.55/min at fal’s launch discount to Nov 7), Seedance 2.5 #3 (1138, $34.12/min), Gemini Omni Flash 1.1 #4 (1132, $9.12/min), Wan 3.0 #5 (1127), MiniMax H3 Max #6 (1125), Seedance 2.0 #7 (1121); AA’s rank ranges put the top 7 within error of one another. Then Veo 3.1 #13 (1028), Kling 3.0 Omni Pro #17 (1004), Kling 3.0 Pro #18 (1000, anchor). The arena measures overall preference, not identity consistency specifically, and Kling 4.0 is not ranked yet. One user’s single-shot test (anecdotal, not the basis of this pick): Kling 4.0 and Kling 3.0 Pro held the character best, Seedance 2.5 had the liveliest motion, Gemini Omni Flash changed the character most. For a recurring character, pass the same reference image (or first and last frame) every time; Kling 4.0 (up to 15) and Wan 3.0 (up to 20) accept several references per request. Sources: artificialanalysis.ai, postcutoff.com, postcutoff.com, fal.ai

Text-to-speech (voice generation, narration)

Pick: Eleven v4 / Eleven v4 Turbo. Alternatives: Qwen-Audio-3.1-TTS (Plus / Flash), Cartesia Sonic-3.6, Gemini 3.8 Flash TTS, Gemini 3.8 Flash-Lite TTS. Open weights: Fish Audio Drama 3. Budget: Speechify Simba 3.2.

Artificial Analysis TTS (Provider Voice Arena): Eleven v4 Turbo 1336 ($40/1M chars) and Eleven v4 1332 ($80), Qwen-Audio-3.1-TTS-Plus 1307 ($19.30), Cartesia Sonic 3.6 1292, Gemini 3.8 Flash TTS 1280 ($16.50), Inworld Realtime TTS-2 1270, Qwen-Audio-3.0-TTS-Plus 1266, Fish Audio Drama 3 Preview 1248 (open weights), Simba 3.2 1246 at $6.60. Both v4 variants are in elevenlabs-v4 (eleven_v4, eleven_v4_turbo). Qwen-Audio-3.1-TTS-Plus has no own registry file (API id unverified), so its 3.0 sibling is listed. Sources: artificialanalysis.ai

Speech-to-text and transcription

Pick: Fun-Realtime-ASR-preview (Fun-ASR-Flash / Fun-ASR-Realtime). Alternatives: Voxtral Small Transcribe 3, MAI-Transcribe-2, Scribe v2 / Scribe v2 Medical, Voxtral Mini Transcribe 3 (+ Mini Transcribe Realtime 3). Open weights: Voxtral Transcribe 2 (Mini Transcribe V2 + Voxtral Realtime). Budget: Voxtral Mini Transcribe 3 (+ Mini Transcribe Realtime 3).

Artificial Analysis speech-to-text (2026-10-25, word error rate): Alibaba Fun-ASR (realtime) #1 at 1.7%, Mistral Voxtral Small Transcribe 3 #3 at 2.1%, Voxtral Mini Transcribe 3 #5 at 2.2% ($0.0035/min). Which Fun-ASR id AA ranked is ambiguous (see the model page). MAI-Transcribe-2 remains strong but is in preview. Field note from a user’s agent (unverified): for timing lyrics to a song, ElevenLabs Forced Alignment drifted on echoes and ad-libs, while Scribe v2 word timestamps (elevenlabs-scribe-v2, $0.22/hour) worked better. Sources: artificialanalysis.ai, postcutoff.com, postcutoff.com

Real-time voice conversation (speech-to-speech agents)

Pick: Grok Voice 3.0. Alternatives: Qwen-Audio-3.1-Realtime (Plus), Gemini 3.8 Live, Eleven Realtime v1 Max / Mini, StepAudio 3 Realtime, GPT-Live-1.1. Open weights: NVIDIA NemotronLabs VoiceChat 11B (and PersonaPlex-7B).

Artificial Analysis speech-to-speech: Grok Voice 3.0 Big Bench Audio 98.5%, Full-Duplex Bench 97.0%, 0.81 s to first audio (Speech-to-Speech Index 86.9, top on Oct 13); StepAudio 3 Realtime scores highest (99.7% / 98.9%) but takes 8.83 s and is preview; Qwen Audio 3.0 Realtime Plus 99.2% / 98.4% at 1.54 s; Eleven Realtime v1 Max 0.57 s (not in registry). GPT-Live-1.1 powers ChatGPT voice but has no API yet (‘coming soon’); use gpt-realtime-2-1 for OpenAI’s API. Sources: artificialanalysis.ai, postcutoff.com, postcutoff.com

Music generation (songs with vocals, instrumentals)

Pick: Suno v6 (v6, v6-wild, v6-mini). Alternatives: Mureka V9.5 (and O3), Lyria 3.5, Eleven Music v2.5. Open weights: MiniMax Music 3.0.

Artificial Analysis Music (vocals): Suno v6 1147, Suno v6-mini 1130, Mureka V9.5 1107, Lyria 3.5 1053, Eleven Music v2.5 1015, MiniMax Music 3.0 1000 (open weights). Suno v6 is the best and has no official API, but it works well through its web app (suno.com) for agents that can drive a browser (e.g. Claude in Chrome or other computer-use agents); creators in our video log commonly pair a language model with Suno this way. For a pure API pipeline use Mureka 9.5 (best via API) or Lyria 3.5 (GA in the Gemini API). Field notes from a user’s agent (unverified, single runs): Suno m4a downloads carry the timed lyrics as a mov_text subtitle track (read it with ffmpeg); Suno v6 ignored a requested tempo (96 BPM asked, about 133 delivered) and a [key change] tag; the wand button next to the style field rewrites the style prompt toward the account’s taste, so skip it when the exact prompt matters. Sources: artificialanalysis.ai, postcutoff.com, postcutoff.com

Embeddings and retrieval (RAG, search)

Pick: Gemini Embedding 2. Alternatives: Cohere Embed 5 Pro, text-embedding-3-large. Open weights: EmbeddingGemma 2. Budget: Cohere Embed 5 Fast.

No current independent leaderboard checked (MTEB snapshots found online were from 2025). Picked on capability: Gemini Embedding 2 embeds text, images, video, audio and PDFs in one space ($0.20/1M); Cohere Embed 5 Pro is strong on visual documents (ViDoRe V3 85.8, vendor) and shares a vector space with Embed 5 Fast; EmbeddingGemma 2 is a 740M open multimodal model (MTEB code 78.68, vendor). Pair with cohere-rerank-4 for reranking. Sources: postcutoff.com, postcutoff.com, postcutoff.com

Text translation and multilingual work

Pick: Gemini 4 Argon. Alternatives: Claude Opus 5.5, GPT-6.1 Sol, Qwen3.8-Max. Open weights: Qwen3.8-Max. Budget: Gemini 3.8 Flash.

Unverified pick: we found no independent October 2026 translation ranking; official WMT26 results are expected after the conference on Oct 28-29, 2026. Choice is by overall capability and language coverage (Gemma/Gemini families cover 140+ languages; Qwen covers Chinese varieties well). Re-check once WMT26 publishes. Sources: artificialanalysis.ai

Live speech-to-speech translation (interpreting)

Pick: Gemini 3.5 Live Translate. Alternatives: GPT-Realtime-Translate, Qwen3.8-LiveTranslate (Flash Realtime).

Vendor specs only: Gemini 3.5 Live Translate (preview) translates audio-to-audio in 70+ languages / 2,000+ pairs and keeps the speaker’s voice; GPT-Realtime-Translate covers 70+ input and 13 output languages; Qwen3.8-LiveTranslate understands 60 and speaks 29 languages with per-speaker voice cloning. No independent comparison found. Sources: postcutoff.com, postcutoff.com, postcutoff.com

Fast and cheap high-volume work (classification, extraction, routing, subagents)

Pick: Claude Haiku 5.5. Alternatives: DeepSeek-V4.1-Flash, MiniMax-M3.1-Flash, GPT-6 Luna, Gemini 3.5 Flash-Lite. Open weights: DeepSeek-V4.1-Flash. Budget: GPT-6 Luna.

Artificial Analysis: Claude Haiku 5.5 (max) 43 at $0.21 per index task and 234 tok/s; DeepSeek V4.1 Flash 45 at $0.26 and 169 tok/s; MiniMax-M3.1-Flash 43 at $0.22; GPT-6 Luna 38 at $0.07 (cheapest); Gemini 3.5 Flash-Lite 22 but 414 tok/s. For raw speed: Mercury 2.5 (714 tok/s on AA) and mercury-3 (diffusion, vendor 1,068 tok/s). Haiku and Luna both cost $0.10/$0.50 per 1M at the low tier. Sources: artificialanalysis.ai, postcutoff.com

Best open-weights model overall (self-hosting)

Pick: MiMo-V2.6-Pro. Alternatives: DeepSeek-V4.1-Flash, GLM-5.3, Kimi K3. Open weights: MiMo-V2.6-Pro. Budget: GLM-5.3-Flash / FlashX.

Artificial Analysis open-weights list: MiMo-V2.6-Pro 46 (MIT, 1.02T/42B active), DeepSeek V4.1 Flash 1017 45, GLM-5.3 45, Step 5 Preview 44, GLM-5.3-Flash 42, Muse Spark Open 39. Kimi K3.1 Pro (55) would lead by 9 points once its weights ship (promised by Nov 4, 2026); Mistral Large 4 weights are promised by end of October. Sources: artificialanalysis.ai, postcutoff.com

On-device and local models (phones, laptops, edge)

Pick: Gemma 4. Alternatives: LFM2.5-24B-A2B, Qwen3.8-27B, Phi-4-Reasoning-Vision-15B. Open weights: Gemma 4. Budget: Liquid AI d1-3B.

No independent on-device ranking checked. Gemma 4 (Apache 2.0) ships E2B/E4B edge sizes with native audio and vision plus 12B-31B sizes; Qwen3.8 27B scores 34 on AA’s open list; Liquid d1 3B answers typed decisions in 8-50 ms. For local embeddings use embeddinggemma-2, for local TTS kokoro-82m. Sources: postcutoff.com, artificialanalysis.ai, postcutoff.com

Computer use and browser agents

Pick: Claude Opus 5.5. Alternatives: Claude Fable 5.1, GPT-6 Astra, GPT-6.1 Sol, Gemini 4 Argon. Budget: Claude Haiku 5.5.

Benchmarks disagree by version: Meta’s table has OSWorld V2.1 (partial) Opus 5.5 81.8, Fable 5.1 80.7, Muse Wonder Full 78.4, GPT-6 Astra 75.8; Google’s table has OSWorld-2.0 offline subset Astra 72.6 vs Argon 69.2, and Agent’s Last Exam Argon 39.5 vs Opus 5.5 38.2 vs Astra 34.2. GPT-6.1 Sol is within 2.1 points of Astra on OSWorld 2.0 at ~1/7 the cost per task (OpenAI). Haiku 5.5 reports OSWorld 2.1 72.4% at $0.10/$0.50. No verified open-weights leader. Sources: postcutoff.com, deepmind.google, postcutoff.com, postcutoff.com

Creative writing: fiction, lyrics, scripts, poetry

Pick: Claude Fable 5.1. Alternatives: GPT-6 Astra, Claude Opus 5.5, GPT-6 Sol, Kimi K3.1 Pro, Grok 4.7, Gemini 4 Argon. Open weights: GLM-5.3. Budget: GPT-6 Sol.

Two independent LLM-judged boards, read 2026-10-25. EQ-Bench Creative Writing v3 (Elo): GPT-6 Astra #1 2174.0, Claude Fable 5.1 #2 2162.7, Claude Opus 5 (legacy) 2133.5, GPT-6 Sol 2124.6, Kimi K3 2083.5, GLM-5.3 2076.7, Claude Opus 5.5 2050.8, Grok 4.7 2012.2 (highest rubric score, 17.16), Gemini 4 Argon only #31 at 1758.0. Lech Mazur’s Short-Story benchmark (lechmazur/writing, 600-800-word stories with 10 required elements, pairwise judged; last update Oct 23, 2026): Fable 5.1 (high) #1 3.745, Opus 5.5 (high) 3.693, Opus 5 (xhigh, legacy) 3.685, GPT-6 Astra (high) #4 3.416 (3rd among current models), GLM-5.3 (max) 2.950, Kimi K3.1 Pro 2.723, Gemini 4 Argon 0.719 (#20), Grok 4.7 0.351 (#26). Fable 5.1 is top-2 on both; best OpenAI is GPT-6 Astra ($10/$50), with GPT-6 Sol ($2/$10) close on EQ-Bench; GPT-6.1 Sol, Sonnet 5.5 and Haiku 5.5 are on neither board. Open: GLM-5.3 ranks above Kimi K3 on the short-story board. EQ-Bench Longform was not used: its table has no model newer than Claude Sonnet 4.6 (Feb 2026). Arena’s creative-writing category returned HTTP 403; Artificial Analysis has no creative-writing index. Song lyrics: Suno and other music models can write lyrics themselves, but a strong LLM usually writes better ones; write them here, then pass them to suno-v6 (see music-generation). Sources: eqbench.com, eqbench.com, github.com

Deep research reports with citations (multi-step web research)

Pick: Gemini Deep Research agent (API). Alternatives: GPT-6 Astra, Claude Opus 5.5, Kimi K3.1 Pro, GPT-6.1 Sol, Gemini 4 Argon, Grok 4.7. Open weights: Ling 3.1 Flash. Budget: GPT-6.1 Sol.

No independent October 2026 ranking of deep-research agents found (FutureSearch’s Deep Research Bench page was last updated June 25, 2026 and shows results only as an image; the DeepResearch Bench Space did not load). Picked on capability: Google’s Deep Research agent is the only dedicated report-writing research agent with an API in the registry (Interactions API, background runs, a Max tier; preview). For a model running its own search loop, BrowseComp as compiled by BenchLM (2026-10-23, mostly vendor-reported): Atria Dawn Preview 92.5% (not in registry), Kimi K3.1 Pro 92.1%, Ling 3.1 Flash 91.7% (open, MIT), GPT-6 Astra 91.5%, Kimi K3 91.2%; no BrowseComp figure found for Claude Opus 5.5, GPT-6.1 Sol, Gemini 4 Argon or Grok 4.7. For long report-style deliverables, AA’s GDPval-AA (agentic, with web browsing) has Opus 5.5 first (1866 Elo). GPT-6.1 Sol has hosted web search and multi-agent delegation in the Responses API at $2/$10. ChatGPT deep research and Claude Research are app features, not API models, and are not in the registry. Sources: futuresearch.ai, benchlm.ai, artificialanalysis.ai, postcutoff.com, postcutoff.com

Tool use and long agent runs (function calling, MCP, multi-step tasks)

Pick: Claude Opus 5.5. Alternatives: Kimi K3.1 Pro, Claude Sonnet 5.5, Gemini 4 Argon, Grok 4.7, GPT-6.1 Sol, GPT-6 Astra. Open weights: DeepSeek-V4.1-Flash. Budget: Claude Haiku 5.5.

Artificial Analysis GDPval-AA v2.1 (220 real work tasks, shell plus web browsing in an agent loop, Elo, read 2026-10-25): Claude Opus 5.5 (max) #1 1866, Muse Wonder Full 1857 (no API price), Kimi K3.1 Pro 1846, Claude Sonnet 5.5 1838, DeepSeek V4.1 Flash 1017 (max) 1746 (open weights), Grok 4.7 (xhigh) 1714, MiMo-V2.6-Pro 1683, Gemini 4 Argon (high) 1624, Claude Haiku 5.5 (max) 1619, GPT-6.1 Sol (max) 1596, GPT-6 Astra (max) 1574. Terminal-Bench 4.0: Opus 5.5 66.4% (vendor), Kimi K3.1 Pro 67% (AA’s highest), GPT-6 Astra 58.2%, Argon 57.4%. Google’s own table has Argon ahead on AutomationBench (51.3% vs Opus 5.5 42.5%, Astra 41.4%) and Vals Finance Agent v2 (65.4% vs 58.6%). Best OpenAI here is GPT-6.1 Sol, not Astra. AA’s tau2-bench Telecom and Terminal-Bench Hard pages show only older models in their text, so no current tau-bench numbers are quoted. Sources: artificialanalysis.ai, artificialanalysis.ai, deepmind.google, postcutoff.com, postcutoff.com

Making a video? Most AI-made videos we logged were built with code, music and voice models rather than a video generator alone: How AI makes video now.

Picks are a snapshot: rankings move every week. When two sources disagree we say so. For any model, the registry page has every provider, id and docs link.