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common : inhibit lazy grammar sampler while reasoning is active (#20970)#1

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Vect0rM merged 5 commits into
feature/turboquant-kv-cachefrom
fix/qwen
Mar 31, 2026
Merged

common : inhibit lazy grammar sampler while reasoning is active (#20970)#1
Vect0rM merged 5 commits into
feature/turboquant-kv-cachefrom
fix/qwen

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@Ooooze

@Ooooze Ooooze commented Mar 30, 2026

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  • common : inhibit grammar while reasoning budget is active

  • cont : update force_pos in accept

  • cont : fix tests

  • cont : tweak should apply logic

  • cont : return early not using grammar sampler

  • Add tests

  • cont : prevent backend sampling when reasoning budget enabled

  • cont : fix typo

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Vect0rM and others added 5 commits March 30, 2026 12:34
@Vect0rM
ci: add GitHub Release with downloadable tar.gz archive
a60b5bd 
Automatically creates a prerelease with the macOS ARM64 binary
on every push to feature/turboquant-kv-cache.

Made-with: Cursor
@Vect0rM
fix: set target_commitish in release action to correct branch
c6b5330 
Without target_commitish, softprops/action-gh-release creates tags
on the default branch (master) instead of the triggering branch.

Made-with: Cursor
@Vect0rM
fix: add BoringSSL static linkage + rpath flags to match release.yml
72da82c 
Without -DLLAMA_BUILD_BORINGSSL=ON, cmake picks up Homebrew OpenSSL
and links dynamically → Team ID mismatch on codesigned macOS apps.

Changes:
- Add -DLLAMA_BUILD_BORINGSSL=ON (static SSL, no dynamic dependency)
- Add -DCMAKE_BUILD_WITH_INSTALL_RPATH=ON (apply rpath at build time)
- Switch to -DCMAKE_INSTALL_RPATH='@loader_path' (consistent with release.yml)
- Add -DLLAMA_BUILD_TOOLS=ON
- Add verification step: otool -L check fails CI if dynamic SSL found

Made-with: Cursor
@Vect0rM
fix: replace BoringSSL with BUILD_SHARED_LIBS=OFF + disable curl/ssl
6879672 
LLAMA_BUILD_BORINGSSL doesn't exist in this fork's CMakeLists.txt —
the flag was silently ignored, binary still linked Homebrew OpenSSL.

Correct approach: disable curl and OpenSSL entirely, build all libs
statically. Produces a single self-contained binary with only system
dylibs (libSystem, libc++, Metal frameworks).

- BUILD_SHARED_LIBS=OFF — links libllama, libggml etc. statically
- LLAMA_CURL=OFF — no curl dependency, no HF model download
- LLAMA_OPENSSL=OFF — no OpenSSL/crypto dependency
- hw.ncpu instead of hw.logicalcpu (correct macOS sysctl key)
- Verification step: fail CI if any non-system dylib found

Made-with: Cursor
@aldehir @pwilkin @Ooooze
common : inhibit lazy grammar sampler while reasoning is active (ggml…
4198d94 
…-org#20970)

* common : inhibit grammar while reasoning budget is active

* cont : update force_pos in accept

* cont : fix tests

* cont : tweak should apply logic

* cont : return early not using grammar sampler

* Add tests

* cont : prevent backend sampling when reasoning budget enabled

* cont : fix typo

---------

Co-authored-by: Piotr Wilkin <piotr.wilkin@syndatis.com>
@Vect0rM Vect0rM force-pushed the feature/turboquant-kv-cache branch from 6879672 to 7b8820c Compare March 31, 2026 08:21
@Vect0rM Vect0rM merged commit d785414 into feature/turboquant-kv-cache Mar 31, 2026
8 of 44 checks passed
Vect0rM pushed a commit that referenced this pull request Apr 21, 2026
@TheTom @claude
fix: TURBO_D=128 independent of QK_TURBO3, file turbo4 bugs #29
6a52a43 
Codex post-commit review found:
1. TURBO_D was QK_TURBO3 (now 32) — broke turbo4 C array sizes
2. SET_ROWS kernel turbo3-specific but instantiated for turbo4
3. Tail block drop for non-128 head dims

Fixed #3 (TURBO_D). #1 and #2 don't affect turbo3+dk128 path.

Co-Authored-By: tturney@psyguard.ai
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Vect0rM pushed a commit that referenced this pull request Apr 21, 2026
@TheTom @claude
final: 12 approaches tested, 4-mag LUT is the hardware limit
9637c1c 
Complete experiment log:
  #1  4-mag LUT:           15.1 at 8K (BEST, +38%)
  #2  Batched extract:     13.7 (+25%)
  #3  Inline FA block:     13.5 (I-cache pressure)
  #4  Deferred norm:       12.9 (loses ILP)
  #5  2-pair half2:        12.0 (ternary overhead)
  #6  Select chain:        11.9 (branches kill)
  #7  Bit-arithmetic:      11.6 (ALU too heavy)
  #8  FMA branchless:      11.4 (ALU still too heavy)
  #9  Named-reg ternary:   10.3 (branches worst)
  #10 Main (8-LUT):        10.95 (baseline)
  #11 Non-vec FA:          10.2 (wrong kernel)
  Ceiling:                 24.5 (no dequant)

Apple8 hardware truth:
  1 divergent constant read < 7 ALU ops (even with fma)
  Branches cost MORE than divergent constant reads
  Array indexing ALWAYS spills on Metal
  4 constant addresses is the sweet spot

The 4-mag LUT is the dequant-level ceiling on Apple Silicon.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Co-Authored-By: tturney@psyguard.ai
@WillowOneVision WillowOneVision mentioned this pull request May 21, 2026
Open
9 tasks
fukuro-kun pushed a commit to fukuro-kun/fukuro-llama-cpp-turboquant that referenced this pull request Jul 5, 2026
@ggerganov @ngxson @slaren
llama : add gpt-oss (ggml-org#15091)
1e9ddf2 
* oai moe

* compat with new checkpoint

* add attn sink impl

* add rope scaling yarn

* logits match with latest transformers code

* wip chat template

* rm trailing space

* use ggml_scale_bias

* rm redundant is_swa_all

* convert interleaved gate_up

* graph : fix activation function to match reference (AtomicBot-ai#7)

* vocab : handle o200k_harmony special tokens

* ggml : add attention sinks support (AtomicBot-ai#1)

* llama : add attn sinks

* ggml : add attn sinks

* cuda : add attn sinks

* vulkan : add support for sinks in softmax

remove unnecessary return

* ggml : add fused swiglu_oai op (AtomicBot-ai#11)

* ggml : add fused swiglu_oai op

* Update ggml/src/ggml-cpu/ops.cpp

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

* update CUDA impl

* cont : metal impl

* add vulkan impl

* test-backend-ops : more test cases, clean up

* llama : remove unfused impl

* remove extra lines

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

---------

Co-authored-by: slaren <slarengh@gmail.com>

* repack mxfp4 upon conversion

* clean up a bit

* enable thinking

* add quick hack to render only some special tokens

* fix bf16 conversion

* remove vocab hack

* webui ok

* support chat parsing for gpt-oss

* fix webui

* direct mapping mxfp4, FINALLY

* force using mxfp4

* properly use lazy tensor

* ggml : add mxfp4

ggml : use e8m0 conversion instead of powf

Co-authored-by: Diego Devesa <slarengh@gmail.com>

change kvalues_mxfp4 table to match e2m1 (AtomicBot-ai#6)

metal : remove quantization for now (not used)

cuda : fix disabled CUDA graphs due to ffn moe bias

vulkan : add support for mxfp4

cont : add cm2 dequant

* ggml : add ggml_add_id (AtomicBot-ai#13)

* ggml : add ggml_add_id

* add cuda impl

* llama : add weight support check for add_id

* perf opt

* add vulkan impl

* rename cuda files

* add metal impl

* allow in-place ggml_add_id

* llama : keep biases on CPU with --cpu-moe

* llama : fix compile error

ggml-ci

* cuda : add fallback for __nv_cvt_e8m0_to_bf16raw

ggml-ci

* cleanup

ggml-ci

* sycl : fix supports_op for MXFP4

ggml-ci

* fix Unknown reasoning format

* ggml-cpu : fix AVX build

ggml-ci

* fix hip build

ggml-ci

* cuda : add mxfp4 dequantization support for cuBLAS

ggml-ci

* ggml-cpu : fix mxfp4 fallback definitions for some architectures

ggml-ci

* cuda : fix version required for __nv_cvt_e8m0_to_bf16raw

---------

Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
Co-authored-by: slaren <slarengh@gmail.com>
fukuro-kun pushed a commit to fukuro-kun/fukuro-llama-cpp-turboquant that referenced this pull request Jul 5, 2026
@dralves
common : Fix corrupted memory error on json grammar initialization (g…
80ae514 
…gml-org#16038)

Initalizing RESERVED_NAME in is_reserved_name() is not thread
safe and leads to corrupted memory when used from multiple threads
as can be seen in the asan trace below. This fixes the initialization
to make it thread-safe.

    #0 0x000100abd018 in std::__1::pair<std::__1::__hash_iterator<std::__1::__hash_node<std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>, void*>*>, bool> std::__1::__hash_table<std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>, std::__1::hash<std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>>, std::__1::equal_to<std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>>, std::__1::allocator<std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>>>::__emplace_unique_key_args<std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>> const&>(std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>> const&, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>> const&) __hash_table:1565
    AtomicBot-ai#1 0x000100ab0320 in SchemaConverter::visit(nlohmann::json_abi_v3_12_0::basic_json<nlohmann::json_abi_v3_12_0::ordered_map, std::__1::vector, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>, bool, long long, unsigned long long, double, std::__1::allocator, nlohmann::json_abi_v3_12_0::adl_serializer, std::__1::vector<unsigned char, std::__1::allocator<unsigned char>>, void> const&, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>> const&) json-schema-to-grammar.cpp:802
    AtomicBot-ai#2 0x000100aafc48 in std::__1::__function::__func<build_grammar(std::__1::function<void (common_grammar_builder const&)> const&, common_grammar_options const&)::$_2, std::__1::allocator<build_grammar(std::__1::function<void (common_grammar_builder const&)> const&, common_grammar_options const&)::$_2>, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>> (std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>> const&, nlohmann::json_abi_v3_12_0::basic_json<nlohmann::json_abi_v3_12_0::ordered_map, std::__1::vector, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>, bool, long long, unsigned long long, double, std::__1::allocator, nlohmann::json_abi_v3_12_0::adl_serializer, std::__1::vector<unsigned char, std::__1::allocator<unsigned char>>, void> const&)>::operator()(std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>> const&, nlohmann::json_abi_v3_12_0::basic_json<nlohmann::json_abi_v3_12_0::ordered_map, std::__1::vector, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>, bool, long long, unsigned long long, double, std::__1::allocator, nlohmann::json_abi_v3_12_0::adl_serializer, std::__1::vector<unsigned char, std::__1::allocator<unsigned char>>, void> const&) function.h:319
    AtomicBot-ai#3 0x000100a2c938 in std::__1::__function::__func<common_chat_params_init_llama_3_x(minja::chat_template const&, templates_params const&, bool)::$_0::operator()(common_grammar_builder const&) const::'lambda'(nlohmann::json_abi_v3_12_0::basic_json<nlohmann::json_abi_v3_12_0::ordered_map, std::__1::vector, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>, bool, long long, unsigned long long, double, std::__1::allocator, nlohmann::json_abi_v3_12_0::adl_serializer, std::__1::vector<unsigned char, std::__1::allocator<unsigned char>>, void> const&), std::__1::allocator<common_chat_params_init_llama_3_x(minja::chat_template const&, templates_params const&, bool)::$_0::operator()(common_grammar_builder const&) const::'lambda'(nlohmann::json_abi_v3_12_0::basic_json<nlohmann::json_abi_v3_12_0::ordered_map, std::__1::vector, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>, bool, long long, unsigned long long, double, std::__1::allocator, nlohmann::json_abi_v3_12_0::adl_serializer, std::__1::vector<unsigned char, std::__1::allocator<unsigned char>>, void> const&)>, void (nlohmann::json_abi_v3_12_0::basic_json<nlohmann::json_abi_v3_12_0::ordered_map, std::__1::vector, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>, bool, long long, unsigned long long, double, std::__1::allocator, nlohmann::json_abi_v3_12_0::adl_serializer, std::__1::vector<unsigned char, std::__1::allocator<unsigned char>>, void> const&)>::operator()(nlohmann::json_abi_v3_12_0::basic_json<nlohmann::json_abi_v3_12_0::ordered_map, std::__1::vector, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>, bool, long long, unsigned long long, double, std::__1::allocator, nlohmann::json_abi_v3_12_0::adl_serializer, std::__1::vector<unsigned char, std::__1::allocator<unsigned char>>, void> const&) function.h:319
    AtomicBot-ai#4 0x000100a139f8 in foreach_function(nlohmann::json_abi_v3_12_0::basic_json<nlohmann::json_abi_v3_12_0::ordered_map, std::__1::vector, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>, bool, long long, unsigned long long, double, std::__1::allocator, nlohmann::json_abi_v3_12_0::adl_serializer, std::__1::vector<unsigned char, std::__1::allocator<unsigned char>>, void> const&, std::__1::function<void (nlohmann::json_abi_v3_12_0::basic_json<nlohmann::json_abi_v3_12_0::ordered_map, std::__1::vector, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>, bool, long long, unsigned long long, double, std::__1::allocator, nlohmann::json_abi_v3_12_0::adl_serializer, std::__1::vector<unsigned char, std::__1::allocator<unsigned char>>, void> const&)> const&) chat.cpp:762
    AtomicBot-ai#5 0x000100a2a7f4 in std::__1::__function::__func<common_chat_params_init_llama_3_x(minja::chat_template const&, templates_params const&, bool)::$_0, std::__1::allocator<common_chat_params_init_llama_3_x(minja::chat_template const&, templates_params const&, bool)::$_0>, void (common_grammar_builder const&)>::operator()(common_grammar_builder const&) function.h:319
    AtomicBot-ai#6 0x000100aa98f4 in build_grammar(std::__1::function<void (common_grammar_builder const&)> const&, common_grammar_options const&) json-schema-to-grammar.cpp:982
    AtomicBot-ai#7 0x0001009c9314 in common_chat_params_init_llama_3_x(minja::chat_template const&, templates_params const&, bool) chat.cpp:1110
    AtomicBot-ai#8 0x0001009b8afc in common_chat_templates_apply_jinja(common_chat_templates const*, common_chat_templates_inputs const&) chat.cpp:1992
    AtomicBot-ai#9 0x0001009b533c in common_chat_templates_apply(common_chat_templates const*, common_chat_templates_inputs const&) chat.cpp:2074
    AtomicBot-ai#10 0x000100810120 in llamacpp_apply_chat_template+0x724 (predict_oai-98384e17fb94e863:arm64+0x100090120)
    ...

==45482==Register values:
 x[0] = 0x00006020004147f8   x[1] = 0x00006080000013c8   x[2] = 0x0000000000000000   x[3] = 0x0000604006289738
 x[4] = 0x0000000000000002   x[5] = 0x0000000000000001   x[6] = 0x04034000004b4000   x[7] = 0x0000000000000001
 x[8] = 0xbebebebebebebebe   x[9] = 0x17d7d7d7d7d7d7d7  x[10] = 0x00000c04000828ff  x[11] = 0x0000000000000001
x[12] = 0x000000002018d383  x[13] = 0x0000000000000000  x[14] = 0xfa0000000000fafa  x[15] = 0x000010700001ffff
x[16] = 0x000000019dc012c0  x[17] = 0x00000001021284f8  x[18] = 0x0000000000000000  x[19] = 0x00000001700acdc0
x[20] = 0x0000000000000002  x[21] = 0x000000002018d384  x[22] = 0x16dd16fd2e731151  x[23] = 0x0000007000020000
x[24] = 0x0000000100c69c08  x[25] = 0x0000000100c69c20  x[26] = 0x00006080000013c7  x[27] = 0x0000000100c69c00
x[28] = 0x00000001700acd60     fp = 0x00000001700aceb0     lr = 0x0000000100abce30     sp = 0x00000001700acd60
AddressSanitizer can not provide additional info.
SUMMARY: AddressSanitizer: SEGV __hash_table:1565 in std::__1::pair<std::__1::__hash_iterator<std::__1::__hash_node<std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>, void*>*>, bool> std::__1::__hash_table<std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>, std::__1::hash<std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>>, std::__1::equal_to<std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>>, std::__1::allocator<std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>>>::__emplace_unique_key_args<std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>> const&>(std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>> const&, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>> const&)
Thread T5 created by T0 here:
    #0 0x0001020b99d4 in pthread_create+0x5c (libclang_rt.asan_osx_dynamic.dylib:arm64e+0x359d4)
    AtomicBot-ai#1 0x000100873910 in std::sys::pal::unix::thread::Thread::new::h77254fdd87a28e05+0x118 (predict_oai-98384e17fb94e863:arm64+0x1000f3910)
    AtomicBot-ai#2 0x0001007c7a1c in test::run_test::haeb3c2bcd5ed6cf6+0x76c (predict_oai-98384e17fb94e863:arm64+0x100047a1c)
    AtomicBot-ai#3 0x0001007aedb0 in test::console::run_tests_console::he9d142d704f3a986+0x149c (predict_oai-98384e17fb94e863:arm64+0x10002edb0)
    AtomicBot-ai#4 0x0001007c5758 in test::test_main::hf86a5e20735245b9+0x118 (predict_oai-98384e17fb94e863:arm64+0x100045758)
    AtomicBot-ai#5 0x0001007c5da0 in test::test_main_static::h61ee9c8fd30abca0+0x54 (predict_oai-98384e17fb94e863:arm64+0x100045da0)
    ...

==45482==ABORTING
fukuro-kun pushed a commit to fukuro-kun/fukuro-llama-cpp-turboquant that referenced this pull request Jul 5, 2026
@TheTom @claude
fix: TURBO_D=128 independent of QK_TURBO3, file turbo4 bugs AtomicBot…
40c4bdc 
…-ai#29

Codex post-commit review found:
1. TURBO_D was QK_TURBO3 (now 32) — broke turbo4 C array sizes
2. SET_ROWS kernel turbo3-specific but instantiated for turbo4
3. Tail block drop for non-128 head dims

Fixed AtomicBot-ai#3 (TURBO_D). AtomicBot-ai#1 and AtomicBot-ai#2 don't affect turbo3+dk128 path.

Co-Authored-By: tturney@psyguard.ai
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
fukuro-kun pushed a commit to fukuro-kun/fukuro-llama-cpp-turboquant that referenced this pull request Jul 5, 2026
@TheTom @claude
final: 12 approaches tested, 4-mag LUT is the hardware limit
3d8b22e 
Complete experiment log:
  AtomicBot-ai#1  4-mag LUT:           15.1 at 8K (BEST, +38%)
  AtomicBot-ai#2  Batched extract:     13.7 (+25%)
  AtomicBot-ai#3  Inline FA block:     13.5 (I-cache pressure)
  AtomicBot-ai#4  Deferred norm:       12.9 (loses ILP)
  AtomicBot-ai#5  2-pair half2:        12.0 (ternary overhead)
  AtomicBot-ai#6  Select chain:        11.9 (branches kill)
  AtomicBot-ai#7  Bit-arithmetic:      11.6 (ALU too heavy)
  AtomicBot-ai#8  FMA branchless:      11.4 (ALU still too heavy)
  AtomicBot-ai#9  Named-reg ternary:   10.3 (branches worst)
  AtomicBot-ai#10 Main (8-LUT):        10.95 (baseline)
  AtomicBot-ai#11 Non-vec FA:          10.2 (wrong kernel)
  Ceiling:                 24.5 (no dequant)

Apple8 hardware truth:
  1 divergent constant read < 7 ALU ops (even with fma)
  Branches cost MORE than divergent constant reads
  Array indexing ALWAYS spills on Metal
  4 constant addresses is the sweet spot

The 4-mag LUT is the dequant-level ceiling on Apple Silicon.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Co-Authored-By: tturney@psyguard.ai
fukuro-kun pushed a commit to fukuro-kun/fukuro-llama-cpp-turboquant that referenced this pull request Jul 12, 2026
docs: ROADMAP + CHANGELOG aktualisiert — M1 teilweise, M2 blockiert
0e746e8 
Status nach Solo-Session 05:00-14:00:
- AtomicBot-ai#2 Tensor Split Regex ✅ angewendet
- AtomicBot-ai#5 GTT Size Tuning ✅ bereits konfiguriert
- AtomicBot-ai#4 n-gram Decoding ⏳ verfügbar, Benchmark ausstehend
- AtomicBot-ai#1 MTP Logits Copy ❌ 19 Konflikte, skipped
- AtomicBot-ai#6 MUL_MAT_ID Subgroup ❌ 23 Konflikte, revertiert
- AtomicBot-ai#7 Vulkan FA Refactor ⏭️ verschoben (abhängig von AtomicBot-ai#6)
- AtomicBot-ai#9 Vulkan Shmem-Staging ❌ PR closed, manuell portieren
fukuro-kun pushed a commit to fukuro-kun/fukuro-llama-cpp-turboquant that referenced this pull request Jul 12, 2026
docs: ROADMAP + CHANGELOG finalisiert — M1 abgeschlossen, M2 blockiert
a7f3b2c 
AtomicBot-ai#4 n-gram Decoding Benchmark (E2B, Mars):
- Baseline: 39.2 t/s, ngram-mod: 39.1 t/s — kein Speedup
- Verfügbar für User, aber kein Default-Speedup auf kleinen Modellen

M1 Status: ✅ abgeschlossen (AtomicBot-ai#2✅ AtomicBot-ai#4✅ AtomicBot-ai#5✅ AtomicBot-ai#1❌)
M2 Status: ⏳ blockiert (AtomicBot-ai#6❌ AtomicBot-ai#7⏭️ AtomicBot-ai#9❌)
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3 participants

@Ooooze @Vect0rM @aldehir