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writing manifest [K
success [K[?25h[?2026l


exec

sshpass -p jetson ssh jetson@192.168.55.1 "ollama run qwen2.5-vl \"Describe a beautiful sunset.\""


Warning: Permanently added '192.168.55.1' (ED25519) to the list of known hosts.
[?2026h[?25l[1G⠙ [K[?25h[?2026l[?2026h[?25l[1G⠹ [K[?25h[?2026l[?2026h[?25l[1G⠸ [K[?25h[?2026l[?2026h[?25l[1G⠸ [K[?25h[?2026l[?2026h[?25l[1G⠴ [K[?25h[?2026l[?2026h[?25l[1G⠦ [K[?25h[?2026l[?2026h[?25l[1G⠦ [K[?25h[?2026l[?2026h[?25l[1G⠇ [K[?25h[?2026l[?2026h[?25l[1G⠏ [K[?25h[?2026l[?2026h[?25l[1G⠏ [K[?25h[?2026l[?2026h[?25l[1G⠋ [K[?25h[?2026l[?2026h[?25l[1G⠹ [K[?25h[?2026l[?2026h[?25l[1G⠸ [K[?25h[?2026l[?2026h[?25l[1G⠸ [K[?25h[?2026l[?2026h[?25l[1G⠴ [K[?25h[?2026l[?2026h[?25l[1G⠦ [K[?25h[?2026l[?2026h[?25l[1G⠧ [K[?25h[?2026l[?25l[?2026h[?25l[1G[K[?25h[?2026l[2K[1G[?25hError: 500 Internal Server Error: model failed to load, this may be due to resource limitations or an internal error, check ollama server logs for details

(Command exited with code 1)


<final>It seems I downloaded the **Qwen3-VL-2B** model correctly (the 1M-context version), but Ollama failed to load it with a generic 500 error. This often happens if the `Modelfile` is too simple for a complex multimodal GGUF, or if Ollama needs specific flags for vision adapters.

I will:
1.  **Check the logs** to see exactly why it crashed (likely memory or GGUF format issue).
2.  **Try a smaller quantization** (Q4_0 instead of Q4_K_M) or simply re-download the non-1M context version if the 1M context is blowing up the KV cache.
3.  Or, since you asked for **Qwen2.5-VL** originally, and I accidentally grabbed Qwen3-VL (my bad), I should probably just get the correct Qwen2.5-VL if that's what you strictly need. But Qwen3-VL is newer.

Actually, let me check the logs first. It might just be a simple configuration fix in the Modelfile.</final>

sshpass -p jetson ssh jetson@192.168.55.1 "journalctl -u ollama -n 50 --no-pager"


Warning: Permanently added '192.168.55.1' (ED25519) to the list of known hosts.
Feb 28 21:50:22 jetson-orin ollama[14545]: llama_context: kv_unified    = false
Feb 28 21:50:22 jetson-orin ollama[14545]: llama_context: freq_base     = 1000000.0
Feb 28 21:50:22 jetson-orin ollama[14545]: llama_context: freq_scale    = 1
Feb 28 21:50:22 jetson-orin ollama[14545]: llama_context: n_ctx_seq (4096) < n_ctx_train (32768) -- the full capacity of the model will not be utilized
Feb 28 21:50:22 jetson-orin ollama[14545]: llama_context:  CUDA_Host  output buffer size =     0.59 MiB
Feb 28 21:50:22 jetson-orin ollama[14545]: llama_kv_cache:      CUDA0 KV buffer size =   144.00 MiB
Feb 28 21:50:22 jetson-orin ollama[14545]: llama_kv_cache: size =  144.00 MiB (  4096 cells,  36 layers,  1/1 seqs), K (f16):   72.00 MiB, V (f16):   72.00 MiB
Feb 28 21:50:22 jetson-orin ollama[14545]: llama_context: Flash Attention was auto, set to enabled
Feb 28 21:50:22 jetson-orin ollama[14545]: llama_context:      CUDA0 compute buffer size =   300.75 MiB
Feb 28 21:50:22 jetson-orin ollama[14545]: llama_context:  CUDA_Host compute buffer size =    12.01 MiB
Feb 28 21:50:22 jetson-orin ollama[14545]: llama_context: graph nodes  = 1231
Feb 28 21:50:22 jetson-orin ollama[14545]: llama_context: graph splits = 2
Feb 28 21:50:23 jetson-orin ollama[14545]: time=2026-02-28T21:50:23.027Z level=INFO source=server.go:1388 msg="llama runner started in 2.62 seconds"
Feb 28 21:50:23 jetson-orin ollama[14545]: time=2026-02-28T21:50:23.027Z level=INFO source=sched.go:566 msg="loaded runners" count=1
Feb 28 21:50:23 jetson-orin ollama[14545]: time=2026-02-28T21:50:23.027Z level=INFO source=server.go:1350 msg="waiting for llama runner to start responding"
Feb 28 21:50:23 jetson-orin ollama[14545]: time=2026-02-28T21:50:23.028Z level=INFO source=server.go:1388 msg="llama runner started in 2.62 seconds"
Feb 28 21:50:24 jetson-orin ollama[14545]: [GIN] 2026/02/28 - 21:50:24 | 200 |  5.390525284s |       127.0.0.1 | POST     "/api/generate"
Feb 28 21:55:36 jetson-orin ollama[14545]: [GIN] 2026/02/28 - 21:55:36 | 200 |     103.011µs |       127.0.0.1 | HEAD     "/"
Feb 28 21:55:42 jetson-orin ollama[14545]: [GIN] 2026/02/28 - 21:55:42 | 201 |  4.075171072s |       127.0.0.1 | POST     "/api/blobs/sha256:858fcf2a39dc73b26dd86592cb0a5f949b59d1edb365d1dea98e46b02e955e56"
Feb 28 21:55:43 jetson-orin ollama[14545]: [GIN] 2026/02/28 - 21:55:43 | 200 |  722.185689ms |       127.0.0.1 | POST     "/api/create"
Feb 28 21:55:54 jetson-orin ollama[14545]: [GIN] 2026/02/28 - 21:55:54 | 200 |      65.473µs |       127.0.0.1 | HEAD     "/"
Feb 28 21:55:54 jetson-orin ollama[14545]: [GIN] 2026/02/28 - 21:55:54 | 200 |    1.374914ms |       127.0.0.1 | GET      "/api/tags"
Feb 28 21:59:08 jetson-orin ollama[14545]: [GIN] 2026/02/28 - 21:59:08 | 200 |      68.322µs |       127.0.0.1 | HEAD     "/"
Feb 28 21:59:13 jetson-orin ollama[14545]: [GIN] 2026/02/28 - 21:59:13 | 201 |  3.874751864s |       127.0.0.1 | POST     "/api/blobs/sha256:0e6ef13c6c41721be6db8ce624111c48a9f26d2592f445ff0e5abf8451d546ff"
Feb 28 21:59:14 jetson-orin ollama[14545]: [GIN] 2026/02/28 - 21:59:14 | 200 |  752.516503ms |       127.0.0.1 | POST     "/api/create"
Feb 28 21:59:18 jetson-orin ollama[14545]: [GIN] 2026/02/28 - 21:59:18 | 200 |      83.874µs |       127.0.0.1 | HEAD     "/"
Feb 28 21:59:18 jetson-orin ollama[14545]: [GIN] 2026/02/28 - 21:59:18 | 200 |  270.306324ms |       127.0.0.1 | POST     "/api/show"
Feb 28 21:59:18 jetson-orin ollama[14545]: time=2026-02-28T21:59:18.908Z level=INFO source=server.go:431 msg="starting runner" cmd="/usr/local/bin/ollama runner --ollama-engine --port 43067"
Feb 28 21:59:19 jetson-orin ollama[14545]: time=2026-02-28T21:59:19.400Z level=INFO source=server.go:247 msg="enabling flash attention"
Feb 28 21:59:19 jetson-orin ollama[14545]: time=2026-02-28T21:59:19.401Z level=INFO source=server.go:431 msg="starting runner" cmd="/usr/local/bin/ollama runner --ollama-engine --model /usr/share/ollama/.ollama/models/blobs/sha256-0e6ef13c6c41721be6db8ce624111c48a9f26d2592f445ff0e5abf8451d546ff --port 33899"
Feb 28 21:59:19 jetson-orin ollama[14545]: time=2026-02-28T21:59:19.402Z level=INFO source=sched.go:491 msg="system memory" total="7.4 GiB" free="6.1 GiB" free_swap="2.7 GiB"
Feb 28 21:59:19 jetson-orin ollama[14545]: time=2026-02-28T21:59:19.402Z level=INFO source=sched.go:498 msg="gpu memory" id=GPU-2f9be16d-5c3d-5744-9d4f-233e0a7f9408 library=CUDA available="5.7 GiB" free="6.1 GiB" minimum="457.0 MiB" overhead="0 B"
Feb 28 21:59:19 jetson-orin ollama[14545]: time=2026-02-28T21:59:19.402Z level=INFO source=server.go:757 msg="loading model" "model layers"=29 requested=-1
Feb 28 21:59:19 jetson-orin ollama[14545]: time=2026-02-28T21:59:19.426Z level=INFO source=runner.go:1411 msg="starting ollama engine"
Feb 28 21:59:19 jetson-orin ollama[14545]: time=2026-02-28T21:59:19.431Z level=INFO source=runner.go:1446 msg="Server listening on 127.0.0.1:33899"
Feb 28 21:59:19 jetson-orin ollama[14545]: time=2026-02-28T21:59:19.436Z level=INFO source=runner.go:1284 msg=load request="{Operation:fit LoraPath:[] Parallel:1 BatchSize:512 FlashAttention:Enabled KvSize:4096 KvCacheType: NumThreads:6 GPULayers:29[ID:GPU-2f9be16d-5c3d-5744-9d4f-233e0a7f9408 Layers:29(0..28)] MultiUserCache:false ProjectorPath: MainGPU:0 UseMmap:false}"
Feb 28 21:59:19 jetson-orin ollama[14545]: time=2026-02-28T21:59:19.486Z level=INFO source=ggml.go:136 msg="" architecture=qwen3vl file_type=Q4_K_M name=Qwen3-Vl-2B-Instruct-1M description="" num_tensors=310 num_key_values=46
Feb 28 21:59:19 jetson-orin ollama[14545]: load_backend: loaded CPU backend from /usr/local/lib/ollama/libggml-cpu.so
Feb 28 21:59:19 jetson-orin ollama[14545]: ggml_cuda_init: GGML_CUDA_FORCE_MMQ:    no
Feb 28 21:59:19 jetson-orin ollama[14545]: ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no
Feb 28 21:59:19 jetson-orin ollama[14545]: ggml_cuda_init: found 1 CUDA devices:
Feb 28 21:59:19 jetson-orin ollama[14545]:   Device 0: Orin, compute capability 8.7, VMM: yes, ID: GPU-2f9be16d-5c3d-5744-9d4f-233e0a7f9408
Feb 28 21:59:19 jetson-orin ollama[14545]: load_backend: loaded CUDA backend from /usr/local/lib/ollama/cuda_jetpack6/libggml-cuda.so
Feb 28 21:59:19 jetson-orin ollama[14545]: time=2026-02-28T21:59:19.556Z level=INFO source=ggml.go:104 msg=system CPU.0.NEON=1 CPU.0.ARM_FMA=1 CPU.0.LLAMAFILE=1 CPU.1.NEON=1 CPU.1.ARM_FMA=1 CPU.1.LLAMAFILE=1 CUDA.0.ARCHS=870 CUDA.0.USE_GRAPHS=1 CUDA.0.PEER_MAX_BATCH_SIZE=128 compiler=cgo(clang)
Feb 28 21:59:20 jetson-orin ollama[14545]: time=2026-02-28T21:59:20.243Z level=INFO source=server.go:3634 msg="http: panic serving 127.0.0.1:58936: runtime error: invalid memory address or nil pointer dereference\ngoroutine 9 [running]:\nnet/http.(*conn).serve.func1()\n\tnet/http/server.go:1947 +0xb0\npanic({0xaaaacf0a73c0?, 0xaaaacfb23c40?})\n\truntime/panic.go:792 +0x124\ngithub.com/ollama/ollama/runner/ollamarunner.(*Server).allocModel.func1()\n\tgithub.com/ollama/ollama/runner/ollamarunner/runner.go:1193 +0x124\npanic({0xaaaacf0a73c0?, 0xaaaacfb23c40?})\n\truntime/panic.go:792 +0x124\ngithub.com/ollama/ollama/ml/nn.(*Conv3D).Forward(0x0, {0xaaaacf25f530, 0x4000e21f40}, {0xaaaacf26cab0?, 0x40012f4018?}, 0x4?, 0x10010100041128?, 0xffff59041a88?, 0xffffa9dd0108?, 0x10?, ...)\n\tgithub.com/ollama/ollama/ml/nn/convolution.go:25 +0x30\ngithub.com/ollama/ollama/model/models/qwen3vl.(*VisionModel).Forward(0x40001420c0, {0xaaaacf25f530, 0x4000e21f40}, {0xaaaacf26cab0, 0x40012f4000}, 0x4000cf09c0)\n\tgithub.com/ollama/ollama/model/models/qwen3vl/model_vision.go:224 +0xdc\ngithub.com/ollama/ollama/model/models/qwen3vl.(*Model).EncodeMultimodal(0x400014bd40, {0xaaaacf25f530, 0x4000e21f40}, {0x4001990000, 0x400436, 0x700000})\n\tgithub.com/ollama/ollama/model/models/qwen3vl/model.go:44 +0xf8\ngithub.com/ollama/ollama/runner/ollamarunner.(*Server).reserveWorstCaseGraph(0x40002250e0, 0x1)\n\tgithub.com/ollama/ollama/runner/ollamarunner/runner.go:1104 +0x294\ngithub.com/ollama/ollama/runner/ollamarunner.(*Server).allocModel(0x40002250e0, {0xfffffd936de1?, 0x0?}, {0x0, 0x6, {0x400051f080, 0x1, 0x1}, 0x1}, {0x0?, ...}, ...)\n\tgithub.com/ollama/ollama/runner/ollamarunner/runner.go:1232 +0x2e4\ngithub.com/ollama/ollama/runner/ollamarunner.(*Server).load(0x40002250e0, {0xaaaacf2508c0, 0x400052ec40}, 0x40004c8280)\n\tgithub.com/ollama/ollama/runner/ollamarunner/runner.go:1311 +0x460\nnet/http.HandlerFunc.ServeHTTP(0x40001438c0?, {0xaaaacf2508c0?, 0x400052ec40?}, 0x400011db10?)\n\tnet/http/server.go:2294 +0x38\nnet/http.(*ServeMux).ServeHTTP(0x10?, {0xaaaacf2508c0, 0x400052ec40}, 0x40004c8280)\n\tnet/http/server.go:2822 +0x1b4\nnet/http.serverHandler.ServeHTTP({0xaaaacf24cbb0?}, {0xaaaacf2508c0?, 0x400052ec40?}, 0x1?)\n\tnet/http/server.go:3301 +0xbc\nnet/http.(*conn).serve(0x40004ca480, {0xaaaacf253008, 0x4000277470})\n\tnet/http/server.go:2102 +0x52c\ncreated by net/http.(*Server).Serve in goroutine 1\n\tnet/http/server.go:3454 +0x3d8"
Feb 28 21:59:20 jetson-orin ollama[14545]: time=2026-02-28T21:59:20.244Z level=ERROR source=server.go:1205 msg="do load request" error="Post \"http://127.0.0.1:33899/load\": EOF"
Feb 28 21:59:20 jetson-orin ollama[14545]: time=2026-02-28T21:59:20.245Z level=INFO source=runner.go:1284 msg=load request="{Operation:close LoraPath:[] Parallel:0 BatchSize:0 FlashAttention:Disabled KvSize:0 KvCacheType: NumThreads:0 GPULayers:[] MultiUserCache:false ProjectorPath: MainGPU:0 UseMmap:false}"
Feb 28 21:59:20 jetson-orin ollama[14545]: time=2026-02-28T21:59:20.245Z level=INFO source=sched.go:518 msg="Load failed" model=/usr/share/ollama/.ollama/models/blobs/sha256-0e6ef13c6c41721be6db8ce624111c48a9f26d2592f445ff0e5abf8451d546ff error="model failed to load, this may be due to resource limitations or an internal error, check ollama server logs for details"
Feb 28 21:59:20 jetson-orin ollama[14545]: time=2026-02-28T21:59:20.290Z level=ERROR source=server.go:304 msg="llama runner terminated" error="signal: killed"
Feb 28 21:59:20 jetson-orin ollama[14545]: [GIN] 2026/02/28 - 21:59:20 | 500 |  1.744676132s |       127.0.0.1 | POST     "/api/generate"


<final>The Ollama logs confirm a crash: `panic serving ... runtime error: invalid memory address or nil pointer dereference`.

This is happening specifically inside `github.com/ollama/ollama/model/models/qwen3vl.(*VisionModel).Forward`, which strongly suggests **Ollama's current version (even the one installed via the script) does not yet fully support the brand new Qwen3-VL architecture**, or at least the specific GGUF format provided by Unsloth.

Since Qwen3-VL is extremely new (released days ago), support in `llama.cpp` and `ollama` is likely experimental or broken.

**Recommendation:**
Let's pivot back to **Qwen2.5-VL-3B-Instruct**. This model is:
1.  Supported by the latest Ollama.
2.  Stable.
3.  Extremely capable for vision tasks.
4.  Fits your hardware.

I will:
1.  Download `Qwen2.5-VL-3B-Instruct-Q4_K_M.gguf`.
2.  Create a Modelfile for it.
3.  Load it into Ollama.

This should work immediately without the experimental crashes of Qwen3-VL.</final>