Strata v0.1.34 发布：新增 Windows AMD 支持与 MCP 服务器

Official release notes (https://github.com/Niko1221/Strata/releases/tag/v0.1.34) **AMD cards on Windows (new), an MCP server so your AI assistant can set Strata up, a shorter README - and a cancelled request now frees the engine within a second.** **AMD on Windows (new, #247 #325):** an AMD card on Windows is set up like an NVIDIA one: double-click `START-HERE.bat`. On a PC with no NVIDIA card Strata can use, setup picks the AMD card by itself and downloads the ready-made AMD engine (`strata-windows-x64-hip.zip`, below). It carries the ROCm libraries it needs, so the AMD driver (AMD Software: Adrenalin Edition) is the only thing to install. Cards: RX 7900 XT / XTX, RX 7800 XT / 7700 XT, RX 9060 XT, RX 9070 / 9070 XT, Radeon AI PRO R9700, RX 6800 / 6900 series. - **This is new:** #325's author ran this port on an RX 9070 XT. Here, the zip's own runtime finds a Radeon iGPU, and a test build of the same code ran a hipBLAS GEMM correctly on it. But the release zip hasn't run a model on a discrete card yet. Please report how it runs (docs/AMD_HIP.md, "Reporting a Windows AMD run"). - **For now on Windows:** one card per model, no images. Linux AMD is unchanged: multi-GPU, and images through the CPU. - Thanks to jagsan-cyber (#247), dvasdekis (#325) and araujoluks (#302) for the Windows work this builds on. **Let your AI set it up (#133):** paste one line into Claude Code, Cursor, Codex or Copilot (in the README). It checks the PC, picks the model, installs, starts and tells you how to connect. `tools/strata_mcp.py` is an MCP server that lets AI tools install, start, check and stop Strata themselves (docs/MCP_SERVER.md). **A shorter README:** what Strata is, how fast it is (now with an AMD PC next to the NVIDIA one), what you need, how to install, which model to pick. The details moved to docs/INSTALL.md, MODELS.md, TROUBLESHOOTING.md and HOW_IT_WORKS.md. AMD is no longer called experimental. **Fixes:** - **A request whose client hangs up is cancelled within about a second** (#430, #431, jkuepker). Before, a non-streamed request ran to `max_tokens`, and a streamed one read its whole prompt, while the next request waited (17-33 s in the reports). - **The prompt path no longer aborts when llama.cpp's MMQ has no tile that fits a card** (`J_best=0`, #420, qni-live). That product takes the FP16 path, and the engine says which type and card. Where everything fits, nothing changes. - **Setup:** - a resumed download needs disk room only for what is still missing (#425, jctaborda); - UD-Q4_K_XL on an AMD card is asked about before its 111 GB download, since it is untested there (#429, jkuepker). - **Docs:** the AMD router's decode gain with a user's repeated measurement next to ours, and their `STRATA_HIP_WMMA=1` numbers (#432, jkuepker). **Checked before the release:** - **Same answers as 0.1.33 on all four quants** (Q2_0, IQ3_XXS, IQ3_S, the Coder), 10/10 each with a fixed cache, including the prompt path's internal state at 4K and 20K tokens. Checked both after the merge and on the final engine. - **The same speed:** 5-pair A/B on Q2_0 and IQ3_S, +1.2 / +0.9 / -0.2 / +0.4%, with the same expert slots. - **Real use at a 57K-token prompt** through the server on Q2_0 and the Coder. A long prompt whose client hung up, followed by a short question: the question was answered in 0.6 s (17 s in #431's report). - **Linux (WSL, RTX 5070):** Q2_0 byte-identical to 0.1.33 (10/10), and the default settings pass. - **AMD on Linux (R9700):** the HIP build of the release and its tests, all passing except the two that need a model fixture or an AVX-512 CPU, as before. The README's AMD numbers were measured on an RX 9070 XT + Ryzen 9 3900X + 47 GB RAM with setup's own install. - **AMD on Windows:** the zip built and packaged. Its `strata-device` with only the zip's libraries lists this PC's integrated Radeon and correctly reports that the engine has no code for it (gfx1036). - **Tests:** setup's (132, including the golden check that NVIDIA `--yes` configs are unchanged), the other tools' and the MCP server's (236 together), the server's (146, including client hang-ups, streamed and not). - **#410:** reproduced on IQ3_XXS: `--pcie-frac 0` was the missing switch for byte-identical repeats (DETAILS.md). **Updating:** get the latest files (`git pull`, or download and unzip anywhere), then run `START-HERE.bat` (Linux: `./setup.sh`). Setup installs engine 0.1.34. The ready-made Strata engines for Windows, which `START-HERE.bat` fetches by itself: - `strata-windows-x64.zip`: NVIDIA (RTX 20 / 30 / 40 / 50: sm_75, sm_86, sm_89, sm_120 + PTX), CUDA 13.0, needs an NVIDIA driver 580 or newer. Contents: `strata.exe`, `strata-vision.exe` (the optional image encoder), `BUILD.json`. - `strata-windows-x64-hip.zip`: AMD (gfx1100, gfx1101, gfx1102, gfx1200, gfx1201, gfx1030), ROCm 10.2.0a20260930 from AMD's TheRock builds, needs a current AMD driver. Contents: `strata.exe`, `strata-device.exe`, `BUILD.json`, `rocm\` (the ROCm libraries and their licenses). Repository README (current repository documentation, not release changes) Strata Run a 125-billion-parameter AI model on your own gaming PC NVIDIA or AMD graphics card (12 GB or more) · Windows or Linux · free and open source A voxel pagoda garden, 1 shot prompt running on an RTX 5070 with Strata (IQ3_S, 128K context) · full video (49 s) Strata runs **[Qwen3.8-Flash-Next](https://huggingface.co/Qwen/Qwen3.8-Flash-Next)** - a large, smart AI model that normally needs a server - on a normal PC. It chats, writes code, reads pictures and works with your apps and coding agents, and nothing leaves your PC. ## How fast is it? Measured on two ordinary gaming PCs. "Writes answers" is how fast the reply appears in a short chat; "reads your prompt" is how fast it takes in what you send (a 32K-token document, code or chat history). A token is about ¾ of a word, so 60 tokens per second is faster than you can read. NVIDIA: RTX 5070 (12 GB), Ryzen 5 7600, 64 GB RAMAMD: RX 9070 XT (16 GB), Ryzen 9 3900X, 47 GB RAM | Size | Writes answers | Reads your prompt | | --- | ---: | ---: | | **Q2_0** | 93 tokens/s | 2,170 tokens/s | | **IQ2_XS** | 79 tokens/s | 2,090 tokens/s | | **IQ3_XXS** | 62 tokens/s | 1,750 tokens/s | | **IQ3_S** | 53 tokens/s | 1,620 tokens/s | | **Coder** | 55 tokens/s | 2,180 tokens/s | | Size | Writes answers | Reads your prompt | | --- | ---: | ---: | | **Q2_0** | 60 tokens/s | 1,160 tokens/s | | **IQ2_XS** | 52 tokens/s | 1,110 tokens/s | | **Coder** | 44 tokens/s | 1,420 tokens/s | A card with more VRAM is faster: an RTX 3090 (24 GB) should write roughly 100-140 tokens per second. Long chats, other cards: [speed of each model](docs/MODELS.md#how-fast-is-each-size), [community results](docs/COMMUNITY_BENCHMARKS.md). Strata is free. If it runs well on your PC, a coffee keeps the work on it going. ## What you need | | | | --- | --- | | **Graphics card** | **NVIDIA** GeForce RTX 20, 30, 40 or 50 series, or **AMD** Radeon RX 7900 XT / XTX, RX 7800 XT / 7700 XT, RX 9060 XT, RX 9070 / 9070 XT, Radeon AI PRO R9700 or RX 6800 / 6900 series - with **12 GB of VRAM or more** | | **RAM** | 32 GB or more - how much decides [which model](#which-model-should-i-pick) fits; 64 GB runs every size | | **Disk** | about 80 GB free, on an SSD if you can (the first start is much faster) | | **System** | Windows 10 / 11 or Linux, and a current graphics driver from NVIDIA or AMD | Everything else is installed for you. Two or three cards can share the model ([multi-GPU](docs/MULTI_GPU.md)). The full list: [docs/INSTALL.md](docs/INSTALL.md#what-you-need). ## Install ### Let your AI set it up Use an AI coding assistant (Claude Code, Cursor, Codex, GitHub Copilot, ...)? Paste this into it: ```text Set up Strata on this PC for me: https://github.com/Niko1221/Strata - follow docs/AI_SETUP.md in that repository. ``` It checks your graphics card, RAM and disk, picks the model that fits, installs it, starts it and tells you how to connect your apps. AI tools can also install, start and stop Strata themselves through its [MCP server](docs/MCP_SERVER.md). ### Or do it yourself [Download Strata](https://github.com/Niko1221/Strata/archive/refs/heads/main.zip) and unzip it (or `git clone` it). **Windows:** double-click **`START-HERE.bat`**. **Linux:** run **`./setup.sh`** in the Strata folder. The same steps for NVIDIA and AMD: the installer finds your card and sets up the right engine for it. It asks which model, which size, how much context (how much text it keeps in mind) and whether it should read pictures - press Enter each time for the recommended answer. Then it downloads the model (~70 GB; you can stop and it continues where it left off) and starts it. Your browser opens the Strata app at `http://127.0.0.1:8080`. > **While the model starts, your PC can be slow or stop responding for 1-3 minutes** (longest the first time): Strata > loads 35-55 GB into your RAM and locks part of it for the graphics card. That's normal - wait, and don't close the > window. The window tells you what it is doing. **Next time**, run `START-HERE.bat` (or `./setup.sh`) again: it starts right away, nothing is downloaded twice. Close its window to stop the model. Updating, Docker, several cards, where the files go and every option: [docs/INSTALL.md](docs/INSTALL.md). ## Which model should I pick? The installer recommends one for your RAM. The same model comes in sizes that are compressed more or less: smaller is faster, larger is a bit smarter. | Your RAM | Take | Why | | --- | --- | --- | | **32 GB** | **Coder** | it fits 32 GB, and it is made for code (with a 24 GB card, Q2_0 and IQ2_XS run too) | | **48 GB** | **IQ2_XS** (or Q2_0, the fastest) | the larger sizes do not fit | | **64 GB** | **IQ2_XS** (recommended), or IQ3_XXS / IQ3_S | every size fits; IQ3_S is the best, and the slowest | | **96 GB or more** | **IQ3_S**, or Unsloth's 4-bit (experimental) | room for the largest sizes with everything else open | - **[Coder](docs/MODELS.md#coder)** - a coding version with half of the experts removed: 91% of the full model's SWE-bench Verified score (by its authors), fits 32 GB of RAM. Weaker outside coding. - **[Swift 1.5](docs/MODELS.md#swift-15)** - a fine-tune that thinks much shorter before it answers, so you get the answer sooner, at about the same quality. - **[Unsloth UD-Q4_K_XL](docs/MODELS.md#unsloth-ud-q4_k_xl-experimental)** (experimental) - the closest to the full model, but most of it is read from the SSD while it answers: 7-8.5 tokens/s on a 64 GB PC. - **[OrcaRouter's Uncensored IQ3_XXS](docs/MODELS.md#orcarouter-uncensored-iq3_xxs)** - a manual setup, not in the installer's menu. Sizes, downloads and what fits where: [docs/MODELS.md](docs/MODELS.md). You can add another model later with `SETUP.bat` (Linux: `./setup.sh --setup`). ## Using it The Strata app's Monitor (left) while a coding agent writes the pagoda garden from the video (right) - **In the browser:** `http://127.0.0.1:8080` - **Chat**, a live **Monitor** of the model and your GPU/CPU/RAM, and **About** with the settings and addresses. - **Your apps and coding agents:** add an "OpenAI-compatible" provider with base URL **`http://127.0.0.1:8080/v1`**, any API key and any model name. Apps that use Anthropic's API: `http://127.0.0.1:8080/v1/messages` (Claude Code: `ANTHROPIC_BASE_URL=http://127.0.0.1:8080`). - **Thinking:** choose **off, low, medium or high** in the chat menu or your app's "reasoning effort". Off is fastest; high is best for hard questions. - **Pictures:** say yes to "Images?" in setup, then click **Picture** in the chat, or attach them in your app (AMD cards: on Linux through the processor, not on Windows yet). - **From your phone or another PC:** `START-HERE.bat --setup --host 0.0.0.0 --api-key ` - always with a key. - **Good to know:** it answers one request at a time. The first message of a chat is read in full (about 1 minute per 30,000 tokens); follow-ups start in seconds. More: [where your chats are stored](docs/INSTALL.md#where-things-are-stored), [the API](docs/DETAILS.md#using-it). ## Something went wrong? - **My PC froze the first time Strata started.** Normal while it loads the model: wait, don't close the window. Still frozen after 10 minutes? Restart the PC, close other programs and try again, or pick a smaller size. - **It stopped while downloading or installing.** Run `START-HERE.bat` (or `./setup.sh`) again: it continues where it stopped. - **It's very slow and the disk light keeps blinking, or "the engine stopped unexpectedly".** Not enough free RAM: close other programs (browsers use a lot), or pick a smaller size (Q2_0 or IQ2_XS). - **It says port 8080 is already in use.** Strata is already running - look for its window. More problems and their fixes: [docs/TROUBLESHOOTING.md](docs/TROUBLESHOOTING.md). Still stuck? Open an [issue](https://github.com/Niko1221/Strata/issues) and attach `strata-.log` from the Strata folder. ## How does it work? Models like this one normally run on servers with hundreds of gigabytes of graphics memory. Your graphics card has 12-24 GB. Strata makes it fit by **sharing the work across your whole PC** - like a kitchen, where the things you use all the time stay on the counter and the rest waits in the pantry. - **The model is a team of 24,576 small specialists ("experts"),** and each word needs only 10 of them. - **Your graphics card** keeps the few thousand experts that are asked most often; **your RAM** holds all of them, and **your processor** works on the rest at the same time. **Your SSD** holds a big lookup table. - **Guess, then check:** a small helper guesses the next few words and the big model checks them all at once, so you get the same answer, 1.6-1.8x sooner. - **Long texts are read in big pieces** (up to 8,192 tokens at a time): over 1,000 tokens per second. The longer explanation: [docs/HOW_IT_WORKS.md](docs/HOW_IT_WORKS.md). Every part and its numbers: [the details](docs/DETAILS.md#how-it-works) and the [paper](docs/paper/Strata-Paper.pdf). ## Credits and license The model is [Qwen3.8-Flash-Next](https://huggingface.co/Qwen/Qwen3.8-Flash-Next) by the Qwen team, compressed by [ISTA-DASLab](https://huggingface.co/ISTA-DASLab/Qwen3.8-Flash-Next-GSQ-RCO-GGUF), UkisAI (Swift 1.5) and Unsloth; Strata is built with parts of [llama.cpp / ggml](https://github.com/ggml-org/llama.cpp). All credits: [docs/HOW_IT_WORKS.md](docs/HOW_IT_WORKS.md#credits). Strata is open source under the [MIT License](LICENSE); a few parts and every model carry their own licenses ([which ones](docs/HOW_IT_WORKS.md#license)). ## Support Strata Strata is free and open source. If it is useful to you, you can support its development: