reasoning model

Fireworks Research has released Ember-1, a reasoning model built on Kimi K3 that produces shorter reasoning traces while claiming comparable output quality. The model offers a 1 million token context window at $3 per 1M input tokens and $15 per 1M output tokens.

Z.ai has released GLM-5.3-Prime, a high-speed variant of its GLM-5.3 model that delivers 1.5-2x the output throughput through inference acceleration while retaining the full 1M-token context window. The model is priced at $2.80 per 1M input tokens and $8.80 per 1M output tokens, targeting coding and long-horizon agentic workloads.

PrismML has released Ternary Bonsai 2 27B, a 27B-parameter reasoning model derived from Qwen3.8-27B that uses ternary weight compression to shrink to roughly 8.5 GB. The model supports a 262K-token context window, image understanding, tool calling, and thinks by default at 'xhigh' reasoning effort.

Meta has released Muse Spark 1.3 Contributor, described as the cost-efficient contributor tier of its multimodal reasoning model line. The model offers a 1 million token context window at $0.10 per 1M input tokens and $0.20 per 1M output tokens, targeting experimentation and early-stage agentic workflows.

Meta has released Muse Spark 1.3, a multimodal reasoning model with a 1M-token context window, listed as free on OpenRouter. The model targets long-running agentic, multi-agent, and coding workflows, though audio input support remains incomplete.

Inception released Mercury 2.5 Preview, a diffusion-based language model that generates tokens in parallel rather than sequentially, claiming throughput of 1,107 tokens per second on standard GPUs. The model is available on OpenRouter with a 260K context window and an 80% launch discount through September 8, 2026.

IBM has released Granite 4.2 8B, a dense reasoning model built for math, code generation, and agentic workflows. The model supports 131K context, 12 languages, and three switchable reasoning modes, priced at $0.10 per 1M input tokens and $0.15 per 1M output tokens.

Alibaba has released Qwen3.8 Flash, a multimodal reasoning model with a 1 million token context window, aimed at coding, agentic workflows, and visual/document analysis. It's priced at $0.16 per 1M input tokens and $0.47 per 1M output tokens through Alibaba Cloud International.

Meta has introduced a discounted 'Contributor' tier of its Muse Spark 1.2 reasoning model, priced at $0.10 per 1M input tokens and $0.20 per 1M output tokens. The lower cost comes with a tradeoff: prompts and outputs may be used to improve Meta's products.

A stealth model called Ox Alpha has appeared on OpenRouter, offering a 1 million token context window at no cost during its preview period. The model's developer remains anonymous, and OpenRouter says it is acting only as a router, not the model's owner or provider.

Z.ai has released GLM-5.3, a large-scale reasoning model aimed at software engineering and long-horizon agent tasks, featuring a 1M-token context window and mandatory reasoning that cannot be disabled. The model is priced at $1.40 per 1M input tokens and $4.40 per 1M output tokens on OpenRouter.

Alibaba's Qwen team has released Qwen3.8-2.4T-A95B-FP8, an open-weight, FP8-quantized MoE model with 2.4 trillion total parameters and 95 billion activated per token. It natively supports 262,144 tokens of context, extensible to 1,010,000, and forms the base for the hosted Qwen3.8-Max API.

Sakana AI has released Namazu, a reasoning model built on Kimi K2.6 and fine-tuned for Japanese language and business contexts. The model offers a 262K token context window at $0.95 per 1M input tokens and $4 per 1M output tokens.

Alibaba has moved Qwen3.8 Max out of preview into general availability, positioning it as the flagship of the Qwen3.8 series with a 1 million token context window and multimodal input support. The model is priced at $2.00 per million input tokens and $6.00 per million output tokens via OpenRouter.

Thinking Machines has released Inkling Small, an open-weights reasoning model with 276 billion total parameters but only 12 billion active. According to Artificial Analysis, it scores nearly as high as the company's larger Inkling model while using roughly a third of the parameters and far fewer output tokens per task.

AMD has released Instella-MoE-16B-A3B-Think, a 16-billion-parameter Mixture-of-Experts language model trained entirely from scratch on AMD Instinct MI300X and MI325X GPUs. The release includes every checkpoint from pre-training through reinforcement learning, along with full training recipes, under a research-only license.

Moonshot AI has released Kimi K2.7 Code, a 1 trillion parameter Mixture-of-Experts model designed for long-horizon coding tasks. The model features a 256K context window and reduces thinking token usage by approximately 30% compared to its predecessor K2.6.