Alex GetmanMga maagang senyal sa AI
FIL

Qwen3.8

Alibaba

Ayon sa mga ulatHindi alam ang petsa ng paglabasNa-update

Takdang panahon

Wala na sa aktibong radar. Hindi kumpirmado ang paglabas o pagpapalit ng pangalang ito.

link sa ebidensiya

  1. · Mga link sa ebidensiya · GitHub search · Alibaba · commits · onprem-ai/deployment-catalog · @tomas-polach
  2. · Mga link sa ebidensiya · GitHub search · Alibaba · commits · finereli/pyramid-mcp · @finereli
  3. · Mga link sa ebidensiya · GitHub search · Alibaba · commits · fdietze/pi-infinite-context · @fdietze
  4. · Mga post ni Alex · pamilya ng mga modelo · GitHub search · Alibaba · commits · agentgateway/agentgateway · @github-actions[bot]
    Sipi
    json.providers.nebius.models["Qwen/Qwen3.8-27B"].name = "Qwen3.8 27B";
  5. · Mga link sa ebidensiya · GitHub search · Alibaba · commits · aabhay007/Personal-AI-Core · @aabhay007
  6. · Mga link sa ebidensiya · GitHub search · Alibaba · commits · QuantumKuba/Diffactly · @QuantumKuba
  7. · Mga link sa ebidensiya · GitHub search · Alibaba · commits · Hallo-ich-bin-PeppaPig/Singularity · @Hallo-ich-bin-PeppaPig
  8. · Mga link sa ebidensiya · GitHub search · Alibaba · commits · Azure/azureml-assets · @hanbitmyths
    Sipi
    Add MAI, Qwen3.8 and Nemotron 3.5 Foundry Local coding models (#5452)
  9. · Mga post ni Alex · pamilya ng mga modelo · GitHub search · Alibaba · pulls · xadupre/devdash-agents · @xadupre
    Sipi
    - Real Qwen3.8 27B on H200-101, physical CUDA 7: streaming generation and a follow-up turn succeeded. Used a temporary configuration with 16 KV blocks and
  10. · Mga link sa ebidensiya · GitHub search · Alibaba · pulls · vllm-project/vllm-torchtpu · @DRZDONG
    Sipi
    [Model][Qwen3.8] qwen38_flash package entry: register() and READMEs
  11. · Mga link sa ebidensiya · GitHub search · Alibaba · pulls · vllm-project/vllm-torchtpu · @DRZDONG
    Sipi
    [Model][Qwen3.8] MTP draft model
  12. · Mga link sa ebidensiya · GitHub search · Alibaba · pulls · vllm-project/vllm-torchtpu · @DRZDONG
    Sipi
    [Model][Qwen3.8] KV offload pool regions
  13. · Mga link sa ebidensiya · GitHub search · Alibaba · pulls · vllm-project/vllm-torchtpu · @DRZDONG
    Sipi
    [Model][Qwen3.8] Runner input adapter
  14. · Mga link sa ebidensiya · GitHub search · Alibaba · pulls · vllm-project/vllm-torchtpu · @DRZDONG
    Sipi
    [Model][Qwen3.8] Hyper-connection layers
  15. · Mga link sa ebidensiya · GitHub search · Alibaba · pulls · vllm-project/vllm-torchtpu · @DRZDONG
    Sipi
    [Model][Qwen3.8] GDN layer input preparation
  16. · Mga link sa ebidensiya · GitHub search · Alibaba · pulls · vllm-project/vllm-torchtpu · @DRZDONG
    Sipi
    [Model][Qwen3.8] Pooled KV cache materialization
  17. · Mga link sa ebidensiya · GitHub search · Alibaba · pulls · vllm-project/vllm-torchtpu · @DRZDONG
    Sipi
    [Model][Qwen3.8] PD transfer: identity, manifest and Raiden connector
  18. · Mga link sa ebidensiya · GitHub search · Alibaba · pulls · vllm-project/vllm-torchtpu · @DRZDONG
    Sipi
    [Model][Qwen3.8] Config hook, geometry checks and pooled cache layout
  19. · Mga link sa ebidensiya · GitHub search · Alibaba · pulls · vllm-project/vllm-torchtpu · @DRZDONG
    Sipi
    [Model][Qwen3.8] PLE feature: tables, host lookup, storage, offload and pooled PLE
  20. · Mga link sa ebidensiya · GitHub search · Alibaba · pulls · vllm-project/vllm-torchtpu · @DRZDONG
    Sipi
    [Model][Qwen3.8] Sequence-parallel prefill backbone
  21. · Mga link sa ebidensiya · GitHub search · Alibaba · pulls · vllm-project/vllm-torchtpu · @DRZDONG
    Sipi
    [Model][Qwen3.8] QSA attention layer
  22. · Mga link sa ebidensiya · GitHub search · Alibaba · pulls · vllm-project/vllm-torchtpu · @DRZDONG
    Sipi
    [Model][Qwen3.8] Model-owned GDN op and layer (no register_oot)
  23. · Mga link sa ebidensiya · GitHub search · Alibaba · pulls · vllm-project/vllm-torchtpu · @DRZDONG
    Sipi
    [Model][Qwen3.8] Per-group Mamba index accessors
  24. · Mga link sa ebidensiya · GitHub search · Alibaba · pulls · vllm-project/vllm-torchtpu · @DRZDONG
    Sipi
    [Model][Qwen3.8] Mamba tail fold: export prefill checkpoints from inside the step
  25. · Mga link sa ebidensiya · GitHub search · Alibaba · pulls · vllm-project/vllm-torchtpu · @DRZDONG
    Sipi
    [Model][Qwen3.8] In-place rows update op
  26. · Mga link sa ebidensiya · GitHub search · Alibaba · pulls · vllm-project/vllm-torchtpu · @DRZDONG
    Sipi
    [Model][Qwen3.8] PLE Torch-to-JAX ops
  27. · Mga link sa ebidensiya · GitHub search · Alibaba · pulls · vllm-project/vllm-torchtpu · @DRZDONG
    Sipi
    [Model][Qwen3.8] QSA Torch-to-JAX ops
  28. · Mga link sa ebidensiya · GitHub search · Alibaba · pulls · vllm-project/vllm-torchtpu · @DRZDONG
    Sipi
    [Model][Qwen3.8] Torch bridge for the QSA kernels
  29. · Mga link sa ebidensiya · GitHub search · Alibaba · pulls · vllm-project/vllm-torchtpu · @DRZDONG
    Sipi
    [Model][Qwen3.8] GDN input preparation kernel
  30. · Mga link sa ebidensiya · GitHub search · Alibaba · pulls · vllm-project/vllm-torchtpu · @DRZDONG
    Sipi
    [Model][Qwen3.8] Unified KV pool kernels
  31. · Mga link sa ebidensiya · GitHub search · Alibaba · pulls · vllm-project/vllm-torchtpu · @DRZDONG
    Sipi
    [Model][Qwen3.8] PLE lookup and gate kernels
  32. · Mga link sa ebidensiya · GitHub search · Alibaba · pulls · vllm-project/vllm-torchtpu · @DRZDONG
    Sipi
    [Model][Qwen3.8] Hyper-connection kernels
  33. · Mga link sa ebidensiya · GitHub search · Alibaba · pulls · vllm-project/vllm-torchtpu · @DRZDONG
    Sipi
    [Model][Qwen3.8] Pooled QSA kernel over the unified KV pool
  34. · Mga link sa ebidensiya · GitHub search · Alibaba · pulls · vllm-project/vllm-torchtpu · @DRZDONG
    Sipi
    [Model][Qwen3.8] QSA KV write kernels (fused, main, compressed)
  35. · Mga link sa ebidensiya · GitHub search · Alibaba · pulls · vllm-project/vllm-torchtpu · @DRZDONG
    Sipi
    [Model][Qwen3.8] QSA union-walk kernels (plan, dense, SparseCore gather, prefill)
  36. · Mga link sa ebidensiya · GitHub search · Alibaba · pulls · vllm-project/vllm-torchtpu · @DRZDONG
    Sipi
    [Model][Qwen3.8] Qwen3.8-Flash model and registration hooks
  37. · Mga link sa ebidensiya · GitHub search · Alibaba · pulls · vllm-project/vllm-torchtpu · @DRZDONG
    Sipi
    [Model][Qwen3.8] QSA main-KV decode context parallelism over rank pairs (DCP-2) kernels
  38. · Mga link sa ebidensiya · GitHub search · Alibaba · pulls · vjmichael/Lu-AI-GUI · @vjmichael
    Sipi
    - Physical interactive owner Windows/Radeon Qwen3.8, Vulkan VRAM/TFFB TTFT p50/p95, and actual local installed MMProj; hosted CPU small models do not substitute.
  39. · Mga link sa ebidensiya · GitHub search · Alibaba · pulls · vitessio/vitess · @jdoupe
  40. · Mga link sa ebidensiya · GitHub search · Alibaba · pulls · nearai/cvm-compose-files · @PierreLeGuen
  41. · Mga link sa ebidensiya · GitHub search · Alibaba · pulls · michsindlinger/specwright · @michsindlinger
  42. · Mga post ni Alex · pamilya ng mga modelo · GitHub search · Alibaba · pulls · SceneWorks/SceneWorks · @michaeltrefry
    Sipi
    SW-7119: Qwen3.8 27B describer model and tier in core, worker, API and catalog
  43. · Mga post ni Alex · pamilya ng mga modelo · GitHub search · Alibaba · pulls · NVIDIA/hyperflare-inference · @Raydius
    Sipi
    The pinned Qwen3.8 Flash Next checkpoint trains a 262,144-token context (theta 10M, interleaved MRoPE 11/11/10). This adds a declared serving variant of the same weights
  44. · Mga link sa ebidensiya · GitHub search · Alibaba · pulls · FlashML-org/FreeToken · @zihaomu
  45. · Mga post ni Alex · pamilya ng mga modelo · GitHub search · Alibaba · pulls · BuQQzz/SHIELD2.0 · @BuQQzz
    Sipi
    Makes Qwen3.8 27B (IQ1_M) a working coding model on an 8 GB card (RTX 2070 SUPER) through SHIELD's own llama-server.
  46. · Mga link sa ebidensiya · GitHub search · Alibaba · pulls · Azure/azureml-assets · @hanbitmyths
    Sipi
    Add MAI, Qwen3.8 and Nemotron 3.5 Foundry Local coding models
  47. · Mga link sa ebidensiya · GitHub search · Alibaba · pulls · 0xburden/modelship · @0xburden
    Sipi
    - Reviewed immutable catalog of 25 standalone Qwen3.8 GGUF quantizations; wizard displays sizes, numeric/letter/full-value selection and a visible UD-Q4_K_M default. No hardware-driven quant substitution; flags
  48. · Mga link sa ebidensiya · GitHub · QwenLM/qwen-code · PR
    Sipi
    - The Standard preset has the same qwen3.8 effort and GLM thinking gaps and will be aligned in a follow-up
  49. · Mga post ni Alex · pamilya ng mga modelo · Alex Getman
    Sipi
    🚨 Qwen3.8 Omni Flash is out It can see, hear and understand video, then actually act on it Give it hours of footage and it can find the right moments, translate, edit or turn it into notes. Give it a meeting and it can pull out tasks and start working on them 1M context, API from $0.43
  50. · Mga post ni Alex · pamilya ng mga modelo · Alex Getman
    Sipi
    🚨 QWEN3.8 FLASH NEXT IS OUT The leaked specs were real: • 125B multimodal MoE • Only 6B active • 262K native context, up to 1M Qwen says it beats Claude Opus 4.6 across coding, agentic tasks, tool use and several multimodal benchmarks.
  51. · Mga post ni Alex · pamilya ng mga modelo · Alex Getman
    Sipi
    🚨 QWEN3.8 FLASH NEXT DROPS TODAY A ModelScope description that was quickly taken down reportedly revealed: • 125B main parameters • 51B N gram embeddings • Only 6B active per token • Multimodal MoE architecture The model is also an official preview of the upcoming Qwen4 architecture.
  52. · Mga post ni Alex · Alex Getman
    Sipi
    ⚡️ Qwen 3.8 27B beat GPT 5.6 Terra This happened in the AA Agentic Index, a benchmark that tests how well models handle agentic tasks. And you can run Qwen 3.8 27B locally on a single RTX 3090.
  53. · Mga post ni Alex · Alex Getman
    Sipi
    ⚡️ Alibaba released Qwen3.8’s weights A model at Claude Opus 4.6 level, a flagship just six months ago, can now run on a single RTX 4090. Qwen3.8 27B uses around 17 GB of VRAM when quantized and should deliver ~50 tok/s.
  54. · Mga post ni Alex · Alex Getman
    Sipi
    Alibaba just teased Qwen3.8 with 2.4T parameters This is the new Qwen flagship, with open weights coming soon. Alibaba ranks it right below Claude Fable 5. Public benchmarks are still missing, so nobody really knows how close it actually is to Fable, or how it stacks up against GPT-5.6 Sol and Kimi K3. Pricing is the fun part. Kimi K3 costs $3/$15, so Qwen3.8 will probably land in the same range. The preview is already live in Qoder. It uses 10x fewer credits during the day and 50x fewer at night, so you can basically test it for free.
Mga espesipikasyon

Qwen3.8 · Wala na sa aktibong radar. Hindi kumpirmado ang paglabas o pagpapalit ng pangalang ito.

Mga tanong

Kailan inilabas ang Qwen3.8?

Hindi alam ang petsa ng paglabas