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Cognition launches new SWE-2 model, Rivaling Fable 5.1 and GPT-Astra

Cognition released SWE-2, a coding model post-trained from Kimi K3 that scores 50.0% on FrontierCode 1.1 Main, near Fable 5.1 at 64% lower cost.

Cognition introduced SWE-2, its most advanced coding model, post-trained from the 2.8T-parameter Kimi K3 base model. It achieves 50.0% on FrontierCode 1.1 Main, 73.0% on DeepSWE 1.1, and 92.8% on Terminal-Bench 2.1, beating Grok 4.6 and SWE-1.7 while matching Fable 5.1 and GPT-5.6 Sol at a fraction of the price. The company says it scaled reinforcement learning to the multi-trillion-parameter regime for the first time, using Pareto-informed cost penalties that train all reasoning-effort levels in a single run, tripled RL environments, and NVFP4/FP8 quantization-aware training. SWE-2 is available today in Devin Desktop and CLI, with rollout on Devin Web and Fusion.

Hacker News · AIupdated 07:28 UTC · 1h agofirst Sep 10, 15:29 UTC · 6d agoModel release 12 sources HN 58↑ · 15 comments1

IFM Releases K2 Horizon: Six Apache 2.0 Models From 0.9B to 375B

MBZUAI's IFM released K2 Horizon, six Apache 2.0 models (0.9B-375B) with open training data, code, and checkpoints, claiming the largest fully open-source launch.

The Institute of Foundation Models (IFM), launched by MBZUAI, released K2 Horizon: six Apache 2.0 models (0.9B, 3.7B, 7B, 32B, 36B-A4B, 375B-A23B) shipping with the ~20-trillion-token pretraining corpus, intermediate checkpoints, training code, and logs, which IFM calls the largest fully open-source launch in AI history. The 375B-A23B scores 70.2 on Terminal-Bench 2.1 and 87.3 on GPQA Diamond; the 7B model posts 70.6 on SWE-bench Verified. New techniques include MoVA, which extends MoE routing into attention (36B total, ~4B active), and Uno, a LoRA adapter giving roughly 3x lossless decoding speedup. IFM's own reward-hacking audit re-scored 375B-A23B from 70.2% to 66.9% after flagging 24 of 712 Terminal-Bench trials.

MarkTechPostSep 7, 05:00 UTC · 10d agoModel release1

[AINews] Muse Spark 1.3 matches GPT-5.6-Sol, confirming Meta Superintelligence as the newest Frontier Lab, >90% discount for training

Meta's Muse Spark 1.3 reportedly ranks as the world's #3 model, matching frontier models from OpenAI and Anthropic with planned open weights.

The Latent Space AI News roundup leads with Muse Spark 1.3, promised in Zuckerberg's letter, which ranks #3 worldwide per AAII, is slated for open weights, and uses a pricing model over 90% cheaper when users opt in to training. The issue also covers the rumored Gemini 3.8 Flash launch and analysis arguing OpenAI's rumored looped-transformer 'Astra' architecture is a modest tweak rather than a breakthrough. Additional coverage includes ByteDance Seed's HarnessDev harness-evaluation benchmark, a retrieval-invoked actual-use evaluation method, Stanford's revamped agent engineering curricula, and Photon 2.1 adding TTS models and NVIDIA B200 support.

Latent SpaceSep 3, 04:38 UTC · 14d agoModel release1

[AINews] Claude Fable/Mythos 5.1: new SOTA model, 75% cache price cut but 70% more output tokens

Anthropic launched Claude Fable 5.1 and Mythos 5.1, claiming new SOTA benchmarks, with 75% cache-read price cut and 1M-token context.

Anthropic released Claude Fable 5.1 and Mythos 5.1 as flagship models for coding and knowledge work, with a 1M-token context window and pricing of $10/$50 per million input/output tokens and cache reads cut 75% to $0.25. Artificial Analysis Intelligence Index scored Fable 5.1 at 66 versus 63 for Claude Opus 5, with HLE at 59.1% and Terminal-Bench v2.1 at 91.4%, though per-task cost rose ~20% due to 1.7x output token usage. Community analysis suggested Fable and Mythos may share underlying weights with different safety/routing behavior, and release notes highlighted Enterprise Frontier Safeguards and zero-data-retention support.

Latent SpaceSep 2, 07:46 UTC · 15d agoModel release2