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Meta's open-weight model Muse Spark Open launches on Fireworks: 816B parameters, 1M context

Meta's open-weight model Muse Spark Open is available on Fireworks from day one of launch. It is an 816B-parameter MoE model that activates 42B parameters per token, with a 1M-token context window, targeting long-horizon coding and agentic tasks. Fireworks says it ranks first among 75 models on Vals AI's Harvey legal agent benchmark with 25.4%, nearly 4 times that of Claude Opus 5 (6.7%); on the Rogo Big Finance Bench it surpasses Claude Opus 5.5 at every difficulty level. Fireworks validated the weights with its own production stack, scoring 91.1% on AIME26, 89.7% on GPQA Diamond, and 84.3% on SWE-bench Verified, and reproduced consistent results with SGLang.

MiniMax M3.1 Flash released: output 200+TPS, price halved

MiniMax released M3.1 Flash, a lightweight model positioned for Coding/Agent optimization, with a 1 million token context, output speed reaching 200+TPS in everyday scenarios, with P50 stable at 170+TPS. Its input price is 1 yuan per million tokens, output 4 yuan per million tokens, and cache read 0.1 yuan per million tokens, roughly half of DeepSeek V4.1 Flash-1017's peak-hour price. On Automation-Bench v1.0.6 it scored 62.2 points, surpassing DeepSeek's 60.5 points; on DeepSWE v1.1 it scored 73.7 points, lower than DeepSeek's 77.0 points.

MiniMax Claims Blind-Test Model Space Bunny, Confirms It as MiniMax-M3.1-Flash

MiniMax officially tweeted to claim the mysterious model Space Bunny on an overseas blind-test platform, confirming it as the upcoming MiniMax-M3.1-Flash. The model had previously drawn developer attention in blind tests with a speed of about 100 words per second and a one-million-token context window; community tests measured generation speed steady at 85 to 112 words per second, and it can run through complex 3D scenes and code builds in a single pass within three minutes, and respond quickly in multi-file project repairs.

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Google Releases Gemini 4 Argon, Limited-Time Half-Price API

Google has released its flagship model Gemini 4 Argon, focused on coding, professional knowledge work, and sustained execution of complex tasks. The API launch price is $2 per million input tokens and $10 per million output tokens, with the discount running through November 30; from December 1, prices return to $4 and $20. On the third-party Artificial Analysis Intelligence Index, Argon High ties with GPT-6 Astra Max and Claude Fable5.1 Max at 53 points, at an average cost of $1.99 per task, about 39% lower than Astra. Google says that on an ADK project it worked unattended continuously for 11 hours, proposed six optimization plans involving 32 files, and ran 16,892 tests, two of which were merged, reducing long-session memory preparation overhead by about 40%.

Meta Releases 816B Open-Source Model Muse Spark Open, Partnering with Apple for Local Execution

Meta has released the open-weight model Muse Spark Open, which uses a MoE architecture with 256 experts, activates about 42B parameters per token, has a context window of 1 million tokens, and supports text, image, video, and audio input but outputs text only. Meta has partnered with Apple to run the approximately 530 GByte four-bit quantized version on two interconnected Mac Studio M5 Ultra machines, distributing computation via the MLX framework and Thunderbolt 5, achieving about 25 output tokens/second at an 8192-token context. Artificial Analysis tests show that it scores 39 on the Intelligence Index, making it the strongest American open-weight model currently available, but it trails MiMo-V2.6-Pro's 46 points and GLM-5.3's 45 points, and ranks last in four Agent tests. The model weights are available on Hugging Face in two versions: 16-bit at approximately 1.6 TByte and four-bit at approximately 530 GByte, with API pricing at $1.25 per million input tokens and $4.25 per million output tokens.

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StepFun open-sources Step 5 Preview, a 600B-parameter MoE model that ranks second on the OpenRouter weekly chart

StepFun officially releases the Step 5 Preview model weights, with BF16 and FP8 versions launched simultaneously on Hugging Face and ModelScope. The model uses a sparse MoE architecture, with 600B total parameters and 27B activated parameters, supports a 1 million Token context window, and scores 44 on Artificial Analysis's Intelligence Index, placing it in the global top three open-source models. As of October 15, 2026, its Token usage ranks second on both the OpenRouter weekly and daily charts, with about 18.8 trillion Tokens used in the past seven days; according to evaluation data at release, its average cost per task is $0.71, about 1/8 that of Claude Opus 5.

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Swiss AI releases the Apertus 1.5 multimodal model, expanding context to 262k tokens

Swiss AI has released Apertus 1.5, which builds on 1.0 by adding native image and audio understanding, a thinking mode, and a 262,144-token context window—4 times larger than 1.0. The model uses early fusion to convert images and audio into discrete tokens and feed them into the same sequence as text; the architecture is unchanged, and it only understands multimodal input while outputting text only. The team says the 8B version outperforms open-source models of the same scale on instruction following and multilingual tasks, its multimodal performance is close to Gemma 4 12B, and it has also released the training data mixture, preference data, and intermediate checkpoints from each stage.

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