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Công ty & mô hình

OpenRouter Mới nhất

Mô hình mới được đưa lên OpenRouter, thay đổi giá và bảng xếp hạng lượt gọi của lập trình viên.

3 tin chọn3 trong 30 ngày quaĐã thu thập 9

Cập nhật 11 tháng 11 08:00

OpenRouter

11 tháng 11Thứ TưMục 1–3 trong 3
  1. OpenRouter Announcements65

    OpenRouter measures the context cost of MCP, CLI and skills on one GitHub task

    OpenRouter measured the same GitHub task across the GitHub MCP server, the gh CLI and a gh skill on Claude Sonnet 5.5, GPT-6 Luna and Gemini 3.8 Flash. On Sonnet 5.5 all three answered correctly, but the CLI used 1,421 input tokens, the skill 3,315 and the MCP server 59,417 with its 46 default tools, whose definitions alone add 19,436 tokens per request. Scoping the server to two tools cut the task to 23,228 tokens, capping results at 4,000 characters brought it to 5,357, and Tool Search cut the up-front cost of 46 tools to under 600 tokens, though it halved the whole-task cost on Sonnet 5.5 while raising it on Claude Haiku 5.5.

    Vì sao đáng chú ý: OpenRouter's measured comparison shows how much context an MCP server, a CLI and a skill each consume on the same GitHub task, and where trimming tool results or deferring definitions changes the bill.

  2. OpenRouter Announcements60

    OpenRouter tests what fp8 and fp4 quantization do to LLM quality and price

    OpenRouter ran 280 exact-answer tasks against six endpoints of Qwen3.8 27B on October 20, 2026 and did not detect an accuracy difference between fp16, fp8 and fp4, with all six scoring between 98.3% and 99.2%. Across 1,455 endpoints, 59.5% report no precision at all and fp8 is the most common labeled format at 23.6%. Lower precision was cheaper for most models but not all, and provider choice moved price more than precision did, with the priciest same-precision endpoint a median 1.72 times the cheapest.

    Vì sao đáng chú ý: OpenRouter measured fp8, fp4 and fp16 endpoints of one model across 240 exact-answer tasks and found no detectable accuracy gap, while price differences tracked the provider more than the precision.

10 tháng 11Thứ Ba
  1. OpenRouter Announcements72

    OpenRouter benchmarks 15 vision models and Mistral OCR on scanned documents

    OpenRouter tested 15 vision models, Mistral OCR and Tesseract on eight self-made degraded scans, and Claude Opus 5.5 was most accurate with 262 of 264 key values correct at $16.42 per 1,000 pages, while Mistral OCR was best value at 258 of 264 for $2.02. On a faded receipt, GPT-6 Luna and GPT-6.1 Sol invented card digits, a server name and wifi passwords, errors that character error rates do not reveal. The post includes code to transcribe scans, turn reasoning off, cross-check two models from different labs and run Mistral OCR through the file-parser plugin.

    Vì sao đáng chú ý: A hands-on benchmark of 15 vision models plus Mistral OCR and Tesseract on eight degraded scans, with runnable code for cross-checking two models to catch fabricated values.