* kv-cache : avoid modifying recurrent cells when setting inputs
* kv-cache : remove inp_s_mask
It was replaced with equivalent and simpler functionality
with rs_z (the first zeroed state) and the already-existing inp_s_copy.
* kv-cache : fix non-consecutive token pos warning for recurrent models
The problem was apparently caused by how the tail cells were swapped.
* graph : simplify logic for recurrent state copies
* kv-cache : use cell without src refs for rs_z in recurrent cache
* llama-graph : fix recurrent state copy
The `state_copy` shuffle assumes everything is moved at once,
which is not true when `states_extra` is copied back to the cache
before copying the range of states between `head` and `head + n_seqs`.
This is only a problem if any of the cells in [`head`, `head + n_seqs`)
have an `src` in [`head + n_seqs`, `head + n_kv`),
which does happen when `n_ubatch > 1` in the `llama-parallel` example.
Changing the order of the operations avoids the potential overwrite
before use, although when copies are avoided (like with Mamba2),
this will require further changes.
* llama-graph : rename n_state to state_size in build_recurrent_state
This naming should reduce confusion between the state size
and the number of states.
* llama : deprecate llama_kv_self_ API
ggml-ci
* llama : allow llama_memory_(nullptr)
ggml-ci
* memory : add flag for optional data clear in llama_memory_clear
ggml-ci
* kv-cache : simplify the "struct llama_kv_cache" interface
ggml-ci
* kv-cache : revert the (n_swa + n_ubatch) change (for next PR)
ggml-ci
* kv-cache : some comments
ggml-ci
* context : fix graph reserve for multiple sequences
ggml-ci
* kv-cache : fix typo [no ci]
* kv-cache : fix find_slot() logic for free slots
ggml-ci
* llama : add TODO for deprecating the defrag API in the future
* kv-cache : improve find_slot() using min/max seq pos info
ggml-ci
* llama : handle aborts and compute errors
ggml-ci
* memory : extract state into llama_memory_state
ggml-ci
* kv-cache : add comments
ggml-ci
* server : update batching logic to reset n_batch on successful decode
* server : upon full re-processing, remove the sequence from the cache
* kv-cache : add TODO for doing split_equal when split_simple fails
ggml-ci
* add distilbert
* small fixes
* add note for LLM_ARCH_DISTIL_BERT
* Use MODEL_ARCH.BERT for DistilBert
---------
Co-authored-by: dinhhuy <huy.dinh@brains-tech.co.jp>
* convert: add support for BertForSequenceClassification
* add support for reranking using BertForSequenceClassification
* merge checks of eos and sep
* fix lint
---------
Co-authored-by: dinhhuy <huy.dinh@brains-tech.co.jp>
* sampling : min-p should always return at least one token
ggml-ci
* sampling : same for typical sampling
* tests : sampling tests use min_keep == 0
ggml-ci
This matches how others do it, but will still avoid the extra
initialization when rope is disabled.
Branch: GraniteFour
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* feat: Add GGUF conversion for granitemoeshared
Branch: GraniteMoEShared
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* feat: hparam and arch plumbing for granitemoeshared
Branch: GraniteMoEShared
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* fix: Split MoE fused tensors for shared experts in conversion
Branch: GraniteMoEShared
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* feat: First WIP cut at model arch in cpp
The hparam and architecture plumbing should be correct, but the
implementation of the shared experts seems to still be broken.
Branch: GraniteMoEShared
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* fix: Cleaner (maybe more correct?) splitting for gate/up
Branch: GraniteMoEShared
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* fix: Fix the input to the shared experts
I had misread that the shared experts take the inputs _before_ the standard
MoE layer and was feeding the output of the MoE to the shared experts.
Branch: GraniteMoEShared
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* fix: Avoid architecture-specific checks for Granite MoE Shared
This is a cleaner way that will allow more flexibility in architecture
strings going forward.
Branch: GraniteMoEShared
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* refactor: Split granite architectures out of llm_build_llama
This helps de-clutter the llama-family graph construction and allows
granite to diverge further (in preparation for Granite 4).
NOTE: I removed the granite scale factors from llm_build_deci because they
appear to only be there as copy-paste from llm_build_llama. The HF config
does not seem to set those values:
https://huggingface.co/Deci/DeciLM-7B/blob/main/config.json
Branch: GraniteMoEShared
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* fix: Fix compiler warning about uninitialized inp_pos
This should not have been reachable, but it warns on some compliers
Branch: GraniteMoEShared
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* fix: Consoladate GraniteMoEShared into GraniteMoE for conversion
Branch: GraniteMoEShared
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* fix: Consolidate GraniteMoEShared into GraniteMoE on the c++ side
Branch: GraniteMoEShared
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
---------
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* llama/ggml: add LLM training support
more compact progress bar
llama_save_model_to_file
llama_opt_param_filter
ggml_graph_dup force_grads
refactor ggml_opt, fix test-opt
* remove logits_all
* refactor CUDA implementation for ACC
* reset graph at beginning of opt period
* Nomic Embed Text V2 with Mixture-of-Experts (MoE) architecture
- Adds MoE-based embedding model supporting multilingual embeddings.
- Selects architecture variant based on hyperparameter detection (MoE layers).
- Removes unnecessary subclass initialization checks for clarity.
https://www.nomic.ai/blog/posts/nomic-embed-text-v2
Co-authored-by: Jared Van Bortel <jared@nomic.ai>
* fix tokenizer
* don't rename this tensor
---------
Co-authored-by: Jared Van Bortel <jared@nomic.ai>
* fix wrong template in GLM4-0414
* fix spaces
* no bos token since it is already in the template
* moved the chatgml4 check to higher priority
* restored template for old GLM models
* moved the GLM4 template check in the correct place with correct check
* Force FP32 compute in cuBLAS GEMM
* Revert "Force FP32 compute in cuBLAS GEMM"
This reverts commit 6efd872732.
* Force F32 compute in GLM4 ffn down
* Edit comment to clarify issue
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
---------
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
* cmake : do not include ./src as public for libllama
ggml-ci
* cmake : rework tests
ggml-ci
* llguidance : remove unicode include
ggml-ci
* cmake : make c++17 private
ggml-ci
* add pixtral text model (vision is wip)
* cgraph ok, just missing 2D RoPE
* fix bad rebase
* first working version
* fix problem with img_break token
* support dynamic image size
* update docs
* update test script
* mtmd : merge `llava-cli` and `gemma3-cli` into single `mtmd-cli`
* support for minicpmv
* remove cpp files of llava and minicpmv
* update hot topics
* mtmd : add not supported msg for qwen2vl
* Update examples/llava/mtmd.cpp
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* graph : make mla compatible with FA
* metal : add exp FA kernels for DeepSeek models
ggml-ci
* llama : minor naming updates
ggml-ci
* ggml : disable FA for DS head sizes
* tests : add FA tests for MLA shapes
ggml-ci
The Granite's FIM tokens are very similar to Qwen's; it's just that
they use underscore instead of a dash. So <fim_middle> for example
instead of <fim-middle>.
Opening up tokenizer_config.json in ibm-granite/granite-3.3-8b-base
shows:
```
"<fim_prefix>",
"<fim_middle>",
"<fim_suffix>",
"<fim_pad>",
...
"<reponame>",
```
* Merged using squash to remove all noise commit messages
* Force flash attention off for `LLM_ARCH_DEEPSEEK2` - embedding too large
* Removed 3 conts (2x RoPE and 1x RMS-norm)
* Changed to use `<cmath>` instead of `<math.h>`
* Reverted removal of the 3 conts
* Used `reshape` in `llm_graph_context::build_attn_mha()`
* Use `k_pe = ggml_reshape`
* Removed the 3 conts again
* Removed the 3D views of `wk_b` and `wv_b`, and just save and 3D in GGUF
* Removed MQA optimisation from `build_attn_mha()` as no gains now
* Simplified `is_mla` branch in `llm_build_deepseek2()`
* Removed `build_attn_mla` and added `nullptr` to all `build_atnn` calls
* Fixed call to `build_attn` in `llm_build_t5_enc`
* Add llama_model_quantize_params parameters
* Add new quantize parameters parsing and validation
* Update usage
* Add new parameters defaults
* Add new quantization parameters logic
* Add llama_model_quantize_params parameters
* Add new quantize parameters parsing and validation
* Update usage
* Add new parameters defaults
* Add new quantization parameters logic
* Minor refactoring as per the contributors' coding guidelines
* Update descriptions to match existing style
* Add llama_model_quantize_params parameters
* Add new quantize parameters parsing and validation
* Update usage
* Add new parameters defaults
* Add new quantization parameters logic
* Minor refactoring as per the contributors' guidelines
* Implement general --tensor-type instead of tensor-specific command option
* Fix implied type bug
* Restore missing #includes
* Add regex capability for tensor selection
* Refactor function name and update ALLOWED_TENSOR_TYPE
* Add missing #include
* Handle edge case when tensor name is cls.output
* Minor logging improvement
* ggml : FA supports F32 V
* graph : cast KV to F16 when the KV cache is not used
ggml-ci
* server : add test that exercises embeddings with FA enabled
ggml-ci
* model : print tensor size during load
* cont : fix units MB -> MiB
Co-authored-by: Diego Devesa <slarengh@gmail.com>
---------
Co-authored-by: Diego Devesa <slarengh@gmail.com>
* vocab : add special infill tokens for CodeLlama
The commit adds the following special tokens for CodeLlama infill:
- `▁<PRE>`
- `▁<SUF>`
- `▁<MID>`
The motivation for this is that currently the infill example uses
CodeLlama as a suggested model. But when using this model the following
error is generated:
```console
/llama.cpp-debug/examples/infill/infill.cpp:165: GGML_ASSERT(llama_vocab_fim_pre(vocab) >= 0) failed
Could not attach to process. If your uid matches the uid of the target
process, check the setting of /proc/sys/kernel/yama/ptrace_scope, or try
again as the root user. For more details, see /etc/sysctl.d/10-ptrace.conf
ptrace: Operation not permitted.
No stack.
The program is not being run.
305251 Aborted (core dumped)
./build/bin/llama-infill -t 10 -ngl 0 -m models/codellama-13b.Q5_K_S.gguf \
-c 4096 --temp 0.7 --repeat_penalty 1.1 -n 20 \
--in-prefix "def helloworld():\n print(\"hell" \
--in-suffix "\n print(\"goodbye world\")\n "
```
* squash! vocab : add special infill tokens for CodeLlama
Add _<EOT> as well.
this allow to use GPU host when possible over CPU repack.
this have the same effect to resolve this issues (#12498) without
completely disable CPU extra buffer.
Co-authored-by: philou <philou@framework>
* ggml : FA with different K, V head sizes (CPU)
ggml-ci
* metal : add FA with HS=192
* metal : extend FA to support different K and V head sizes
ggml-ci
* metal : add FA vector kernels for heads K 192 and V 128
ggml-ci
* ggml : restrict op on other backends to equal head sizes
ggml-ci
* metal : optimize FA-vec kernel
ggml-ci
* metal : FA remove mq registers
* metal : improve MoE mul_mat_id condition
ggml-ci
* metal : fix comments + remove unnecessary addition
ggml-ci
* metal : avoid too much shared memory usage with mul_mat_id
ggml-ci
* add edgellm model arch[conversation feature doesn't work]
* remove output.weight layer for edgellm arch
* [Model] update the name of the model
* update the name of model arch in convert gguf
* [Model] Refarctor the model arch into llama-model
* [Bug] Fix the bug in create attn kv
* [Code] Fix editorconfig erros
* [Code] Remove Trailing whitespace
* [Code] Remove Trailing whitespace
* [Code] Change the order of model arch in list
* [Code] Fix flake8 Lint errors
* Remove trailing white space
* [Code] Remove call in model arch
* Add support for GPT2, Bloom and CodeShell tied word embeddings
* Deduplicate tied word embeddings weights
* Workaround for incorrect weight map
It appears transformer.wte.weight is in the weight map even though the weights are not there, remove it if output weights are encountered first.
* check++
* fatfingers--
* graph : normalize Q, K, V shapes and add comments
ggml-ci
* context : synchronize before getting cross attention data
* model : fix command-r attention norm check
* llama : introduce llama_set_warmup() API call that controls warmup mode; use all MoE experts during warmup
* common : use new API to enable warmup mode during model warmup
---------
Co-authored-by: Stanisław Szymczyk <sszymczy@gmail.com>
* sampler: turn lazy grammar trigger words to regexes
* add scripts/tool_bench.sh & .py
* constrain llama json output regardless of function name if matches at beginning
* update relaxed newline space rule in grammar tests
* support add_generation_prompt query parameter (useful for /apply_template)
* Update src/llama-grammar.cpp
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* llama : add xcframework build script
This commit adds a script to build an XCFramework for Apple
ios, macos, visionos, and tvos platforms.
The generated XCFramework can then be added to a project and used in
the same way as a regular framework. The llama.swiftui example project
has been updated to use the XCFramework and can be started using the
following command:
```console
$ open examples/llama.swiftui/llama.swiftui.xcodeproj/
```
Refs: https://github.com/ggml-org/llama.cpp/issues/10747
* examples : remove llama.cpp (source dir ref) from project.pbxproj
This commit removes the reference to llama.cpp from the project.pbxproj
file since Package.swift has been removed.
* ci : updated build.yml to use build-xcframework.sh
* ci : add xcframework build to github releases
This commit adds the ability to create a GitHub release with the
xcframework build artifact.
* scripts : add apple app validation scripts
This commit adds scripts that can validate the iOS, macOS, tvOS, and
VisionOS applications. The scripts create a simple test app project,
copy the llama.xcframework to the test project, build and archive the
app, create an IPA from the archive, and validate the IPA using altool.
The motivation for this is to provide some basic validation and
hopefully avoid having to manually validate apps in Xcode.
* llama : remove Package.swift
This commit removes the Package.swift file, as we are now building an
XCFramework for the project.
* llama : remove Sources and spm-headers directories
* llama : use TargetConditionals.h for visionOS/tvOS
* Add include files for std::min/max and std::toupper/tolower
* win32: move _USE_MATH_DEFINES before includes to ensure M_PI is defined
* Use GGML_RESTRICT instead of "restrict" keyword everywhere, and use "__restrict" in MSVC plain C mode
* win32: only use __restrict in MSVC if C11/C17 support is not enabled
---------
Co-authored-by: Marcus Groeber <Marcus.Groeber@cerence.com>
* Added Phi-4-mini-instruct support
* Update regex per ngxson
* Change the vocab base to Xenova/gpt-4o
* fix conversion update script
* no need to check longrope
* minor style fix
* fix python style
---------
Co-authored-by: Nicholas Sparks <nisparks@microsoft.com>
It's useful to be able to have this from the library layer as it's a key
parameter of the model (e.g. to figure out how much KV cache memory is
needed).
This commit adjusts the indentation for the functions `parse_sequence`
and `parse_rule` in src/llama-grammar.cpp.
The motivation is consistency and improve readability.
* extract & return thoughts in reasoning_content field (unless --reasoning-format) for DeepSeek R1 & Command R7B
* tool-calls: add deepseek r1 template (models/templates/llama-cpp-deepseek-r1.jinja) + hackommodate broken official template
* tool-calls: accommodate variety of wrong tool call opening tags both R1 Qwen 32B and 7B distills like to spit out
* server/oai: ensure content is null when there are tool calls, and reasoning_content appears before content for readability
* tool-calls: add DeepSeek R1 Qwen distills to server/README.md & server tests
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
Technically the fixed width types come only from iostream and
cstdint/stdint.h headers. memory and vector headers should not provide
these. In GCC 15 the headers are cleaned up and you require the proper
header cstdint.
src/llama-mmap.h:26:5: error: ‘uint32_t’ does not name a type
26 | uint32_t read_u32() const;
| ^~~~~~~~
Silently insert U+FFFD(s) (Unicode replacement character) instead until the
next valid codepoint can be found.
This fixes `llama_tokenize` throwing an exception across the C API boundary
or libllama's module boundary (the caller's runtime might be incompatible!)
Returing a proper error code might be desirable, however the signature
of `llama_tokenize` doesn't allow it as all return values already have
existing meaning.
* Update llama.cpp
For display progress dots in terminal.
Without this it didn't display dots progress during loading model from file.
* Update llama.cpp
removed trailing spaces
The C API in llama.h claims users can implement `llama_sampler_i` to
create custom `llama_sampler`. The sampler chain takes ownership and
calls `llama_sampler_free` on them. However, `llama_sampler_free` is
hard-coded to use `delete`. This is undefined behavior if the object
wasn't also allocated via `new` from libllama's C++ runtime. Callers
in C and C-compatible languages do not use C++'s `new` operator. C++
callers may not be sharing the same heap as libllama.
* add glm edge chat model
* use config partial_rotary_factor as rope ratio
* support for glm edge model
* vision model support
* remove debug info
* fix format
* llava.cpp trailing whitespace
* remove unused AutoTokenizer
* Update src/llama.cpp for not contain <|end|> or </s>
Co-authored-by: Xuan Son Nguyen <thichthat@gmail.com>
* add edge template
* fix chat template
* fix confict
* fix confict
* fix ci err
* fix format err
* fix template err
* 9b hf chat support
* format
* format clip.cpp
* fix format
* Apply suggestions from code review
* Apply suggestions from code review
* Update examples/llava/clip.cpp
* fix format
* minor : style
---------
Co-authored-by: liyuhang <yuhang.li@zhipuai.cn>
Co-authored-by: piDack <pcdack@hotmail.co>
Co-authored-by: Xuan Son Nguyen <thichthat@gmail.com>
Co-authored-by: liyuhang <yuhang.li@aminer.cn>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
---------
Co-authored-by: Xuan Son Nguyen <thichthat@gmail.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
* impl::load change map bpe_ranks to onordered map for reduce time of impl::load on 30%
* llama_model_loader::init_mapping - replace new llama_mmap to std::make_unique<llama_mmap> for clean code & reduce (/2) time of running init_mappings
* Update src/llama-vocab.cpp
---------
Co-authored-by: lexasub <empty@empty.ru>
Co-authored-by: Diego Devesa <slarengh@gmail.com>
This commit removes the 'd' from the log message in llama-vocab.cpp
when logging a bad special token.
The motivation for this is that currently the output can look something
like the following:
```console
load: bad special token:
'tokenizer.ggml.image_token_id' = 128256d, using default id -1
```
* (wip) support mergekit-extracted lora
* support mergekit-extract-lora
* use lora->get_scale
* correct comment
* correct norm name & condition
* add some hints
* GGUF: C++ refactor, backend support, misc fixes
remove ggml_tensor.backend
update CODEOWNERS [no ci]
remove gguf_get_data from API
revise GGUF API data types
This commit renames the `batch` parameter to `ubatch` in the
`llama_kv_cache_find_slot`, `llm_build_inp_embd`, and
`llm_build_mamba` functions.
The motivation for this is that this should have been done as part of
Commit 19d900a756 ("llama : rename batch
to ubatch (#9950)") but for some reason I missed these functions in
that commit and only noticed them now (sorry).
* convert : extend DEEPSEEK2 model architecture to support DeepseekV3ForCausalLM by adding EXPERT_WEIGHTS_NORM and EXPERT_GATING_FUNC model parameters and FFN_EXP_PROBS_B tensor type
* vocab : add DeepSeek V3 pre-tokenizer regexes
* unicode : handle ACCENT_MARK and SYMBOL categories in regex
* llama : add DeepSeek V3 chat template, handle new model parameters and tensor types
---------
Co-authored-by: Stanisław Szymczyk <sszymczy@gmail.com>
* Add Falcon3 model support
* Add fix for adding bos to added special tokens
* Add comment explaining the logic behind the if statement
* Add a log message to better track the when the following line of code is triggered
* Update log to only print when input and output characters are different
* Fix handling pre-normalized tokens
* Refactoring
* convert : use GPT2 vocab for Phi-4 model
* convert : use null value of sliding_window to distinguish Phi-4 from other PHI3-based models
* llama : do not use sliding window attention mask for Phi-4 model
---------
Co-authored-by: Stanisław Szymczyk <sszymczy@gmail.com>
* sampling : refactor + optimize penalties sampler
ggml-ci
* common : apply ignore_eos as logit bias
ggml-ci
* batched : remove penalties sampler
* params : allow penalty_last_n == -1 to be equal to context size
ggml-ci
* common : by default, move the penalties at the end of the sampling chain
ggml-ci
* common : ignore all EOG tokens
Co-authored-by: Diego Devesa <slarengh@gmail.com>
* common : move back the penalties at the front of the sampling chain
ggml-ci
* readme : restore hint about --ignore-eos flag [no ci]
* llama : minor
ggml-ci
* webui : update
---------
Co-authored-by: Diego Devesa <slarengh@gmail.com>
* Add deepseek v1 arch & gigachat template
* improve template code
* add readme
* delete comments
* remove comment
* fix format
* lint llama.cpp
* fix order of deepseek and deepseek2, move gigachat temlate to the end of func
* fix order of deepseek and deepseek2 in constants; mark shared exp as deepseek arch need
* remove comments
* move deepseek above deepseek2
* change placement of gigachat chat template
* rename ggml-cpu-aarch64.c to .cpp
* reformat extra cpu backend.
- clean Q4_0_N_M and IQ4_0_N_M
- remove from "file" tensor type
- allow only with dynamic repack
- extract cpu extra bufts and convert to C++
- hbm
- "aarch64"
- more generic use of extra buffer
- generalise extra_supports_op
- new API for "cpu-accel":
- amx
- aarch64
* clang-format
* Clean Q4_0_N_M ref
Enable restrict on C++
* add op GGML_OP_MUL_MAT_ID for Q4_0_N_M with runtime repack
* added/corrected control on tensor size for Q4 repacking.
* Update ggml/src/ggml-cpu/ggml-cpu-aarch64.cpp
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* Update ggml/src/ggml-cpu/ggml-cpu-aarch64.cpp
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* add debug logs on repacks.
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* llama : add enum for supported chat templates
* use "built-in" instead of "supported"
* arg: print list of built-in templates
* fix test
* update server README
* Templates: `mistral-v1`, `mistral-v2`, `mistral-v3`, `mistral-v3-tekken`
* Changed system message logic and added tests for all 4
* Invalid `system_message` instead of `content` fixed
* Removed tab-indented lines
* Added template code and test for `mistral-v7`
* Added all tests. Fixed bug with `tmpl == "llama2"` test.
* Replaced tabs with spaces.
* Removed `'mistral-v2'` option as no (open) models ever used it
* Removed all references to 'v2' template from comments
* Update llama.cpp
Fixed `trim_assistant_message` bug
Guy Goldenberg
Georgi Gerganov
Đinh Trọng Huy
compilade
Sigbjørn Skjæret
Diego Devesa
Xuan-Son Nguyen
zhangkaihuo
Piotr Jasiukajtis
Olivier Chafik
0cc4m
Gilad S.
Gabe Goodhart
Ed Addario
Johannes Gäßler
David Huang
piDack
DocShotgun
oobabooga
ymcki
Jared Van Bortel
matteo
ddh0
AT
pockers21
City
Mikko Juola
Juk Armstrong
Yuxuan Zhang
Bo Zheng
Plamen Minev
yumeyao
jklincn
Daniel Bevenius
Juyoung Suk
Sergei Vorobyov
Djip007
Si1w
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