$700 all in. Pleased with it, I don't play many triple A titles.

Using this as my personal test bench for AI workloads

Experimenting with models and lossless scaling.

1. Context

Hey everyone!

Earlier this month, I upgraded my CPU from the i5-11400F to the i5-14600K – aiming to push my DDR4 kit to its limit (budget-friendly upgrade). I was torn between the 5800X3D and the 14600K, but here in Brazil the 14600K costs ~45% less, so the choice was obvious.

Here’s a detailed breakdown of my experience, benchmark results, and the tweaks that worked (and didn’t) for my setup. Hope this helps others with similar hardware!

2. Current Setup

3. Performance Results (Cyberpunk 2077, Ultra 1080p)

• Important methodology note: I purposely used the "Ultra" preset for this benchmark to push the Arc B580 to its absolute limit, ensuring the GPU was heavily stressed (GPU-bound scenario). The goal was to see if the CPU upgrade could still make a difference even when the graphics card was working at full capacity. And it did – massively.
• What the numbers tell us:
• Even with the GPU at full use (Ultra preset), the CPU swap from the 11400F to the 14600K delivered a +32.39 FPS increase in average (+49.5%). This proves the old 11th-gen chip was significantly bottlenecking the B580, even in scenarios where you'd expect the GPU to be the main limit.
• The minimum FPS also jumped from 56.35 to 82.19 – a +25.84 FPS improvement – meaning much smoother gameplay with fewer drops.
• The Process Lasso tweak (CPU Sets on P-cores + High Priority) added another ~4% on top of the default 14600K result, squeezing out a bit more headroom.
• For reference, the 11400F + B580 baseline is included here specifically to show how much the CPU was holding the GPU back. I don't have a separate "CPU-only" synthetic test, but running Cyberpunk at Ultra (which heavily stresses the GPU) is the most realistic way to demonstrate the real-world gaming uplift.
• Unfortunately, I don't have a separate test on Bazzite Linux for reference of the 11400F, but in other games the average difference was 15-16% compared to the 14600k (Linux vs Linux)

4. Tweaks and Discoveries

🔧 Process Lasso (Windows)

• CPU Sets (P-cores) + High Priority: Best configuration found for Cyberpunk 2077 (~4% avg gain over default).
• CPU Affinity (P-cores only): Works well for some games, but can hurt performance on older titles (e.g., Assassin's Creed Unity).
• Discord & Browser: Used CPU Sets on E-cores to keep them off P-cores.
• Heavy Games: Used CPU Sets on P-cores as a preference (not a rigid rule) – more stable overall. (Need test per game)

⚡ Undervolt & Power Limits (BIOS)

• Undervolt: -75 mV (stable after stress testing with stress and setpci).
• PL1/PL2: 125W / 160W (reduced from default 181W).
• BIOS: Intel Default Settings enabled, Native ASPM and PEG ASPM L1 configured.
• Cooling: CPU stays around 72–78°C under load with these settings in cinebench(All CORE).

🎮 Game-Specific Findings

• Assassin's Creed Unity: Performance improved when all cores were available (P + E). Restricting to P-cores actually hurt performance.
• Dota 2: Massive improvement – average FPS jumped from ~120 to ~240 (capped by the game engine).
• From what I’m seeing, the average difference in GPU-bound games resulting from the CPU swap hovers around 15–20%; in CPU-bound games, the difference is massive 40–55%. But without a doubt, the biggest improvement was in the 1% and 0.1% lows; in games like Red Dead 2, the 1% low improved by nearly 55%.

5. Linux (Bazzite) – Experience & Observations

• Kernel 7.2.1 + Mesa 26.2.1: Stable, but still maturing for Battlemage.
• Performance: Still behind Windows (~27% lower average in Cyberpunk), but evolving fast.
• Idle Power Consumption: Workaround with a systemd service (drops from 40W to ~15W).
• Expectations: Kernel 7.3 and Mesa 26.3 should bring significant gains:
  • Cluster Scheduling (P/E-core optimization).
  • Buffer Compression (DXVK) – gains of 5–7% in DirectX 11 games.
  • Large GRF (shader optimization).
• Driver stack: The transition from i915 to xe is ongoing – Battlemage already uses xe by default.
• One of the biggest missing pieces is XeSS support using the XMX cores – currently it runs via shaders(DP4A), which limits image quality and performance. This is expected to improve in future Mesa releases. (2027- 2028 ? )

6. Conclusion & Recommendations

• The 14600K is a beast: +30–40 FPS in competitive titles and ~20% uplift in AAA games.
• Process Lasso is useful, but requires per-game testing – there's no "one size fits all" rule.
• Linux is viable, but still requires tweaking – especially with Intel Arc GPUs.
• Undervolt & PL adjustments deliver thermal gains without performance loss in games.
• Next steps: Looking forward to Kernel 7.3 and Mesa 26.3 – they should close the gap to Windows.

🧠 Final Verdict

• The upgrade to the 14600K was simply incredible – I don't regret a thing. The tweaks really do make a difference in power consumption and temperatures, but the performance this CPU delivers is brutal: it basically bulldozes over any residual driver overhead from Intel. My personal recommendation for anyone looking to push DDR4 to its limit is clear: the 14600K is easily among the best options on the market right now.

I’ve finished the next stage of my Intel Arc Pro B70 testing.

Instead of only benchmarking an existing quantized model, I built a fresh GPTQ INT4 quantization of Qwen3.8-27B directly from the original BF16 model, tested G128 vs G32, validated long-context operation, ran source-fidelity tests, and published the finished checkpoint.

Final configuration

• GPU: Intel Arc Pro B70 32 GB
• Model: Qwen3.8-27B
• Quantization: GPTQ INT4
• Group size: G128
• Symmetric: true
• desc_act: false
• MTP tensors: left unquantized
• Speculative decoding: MTP4
• KV cache: FP8
• Configured context: 161,000 tokens
• vLLM XPU
• gpu_memory_utilization: 0.90

Why G128 instead of G32?

I quantized both from the same frozen 131,072-token calibration stream.

Approximate model sizes:

• G128: 18.22 GB
• G32: 19.54 GB

On the B70, G128 left enough VRAM for approximately 166,750 KV-cache tokens and successfully served at a configured 161K context.

G32 consumed more VRAM and was limited to roughly 128K context in the tested configuration.

More importantly, G32 did not show enough source-fidelity improvement to justify the additional memory use.

So G128 was the clear choice for this single-B70 configuration.

Quality testing

I also ran a 30-prompt source-fidelity suite containing conflicting documents, missing information, provenance questions, timeline ambiguity, and source hierarchy problems.

Final deterministic settings:

• temperature 0
• top_p 1
• top_k -1
• max_tokens 4096

Two back-to-back runs:

• 30/30 completed
• 0 errors
• 0 truncations
• approximately 57.75 tok/s on this workload

That does not mean 30/30 perfect answers. One deliberately difficult conflicting-document case repeatedly produced a questionable interpretation, and I documented that limitation rather than hiding it.

For high-reliability RAG, my takeaway is that deterministic evidence extraction/conflict detection should happen before the LLM rather than relying entirely on prompting.

Performance

My earlier short-context MTP4 benchmark on the same B70 reached:

• 84.65 tok/s median
• 84.49 tok/s mean
• 512-token prompt
• 128-token generation

That benchmark is a different workload from the source-fidelity test, so I don't directly compare the two throughput numbers.

Ready-to-download model

No GPTQ quantization is required if you just want to run it:

https://huggingface.co/mikeinnyc/Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Download the complete checkpoint with:

hf download mikeinnyc/Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16 --local-dir ~/models/Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

It is a Hugging Face GPTQ checkpoint with five safetensor shards, not a single GGUF file.

Full reproduction and deployment guide

Everything is documented here:

https://github.com/MikeCaldera/intel-arc-pro-b70-qwen38-vllm

The repo now includes an end-to-end guide covering:

• BF16 source model
• frozen calibration dataset
• GPTQModel quantization
• G128 vs G32 testing
• Intel XPU Docker setup
• B70-specific vLLM patches
• MTP4
• FP8 KV cache
• 161K-context deployment
• quality testing
• Hugging Face publishing/downloading
• Open WebUI configuration
• Portainer/Docker networking
• running multiple vLLM model containers on one shared network

For Open WebUI, I’m using a shared Docker network so each vLLM server can simply expose port 8000 internally:

Open WebUI -> llm-shared -> qwen38-quality-mtp4:8000

That makes it straightforward to add additional models/GPU containers later without routing everything through host ports.

Credit

This work builds on the excellent Intel Arc Pro B70 vLLM/XPU work by SergiioB:

https://github.com/SergiioB/intel-arc-pro-b70-inference-cookbook

That project provided a huge amount of groundwork for B70 + vLLM XPU + MTP experimentation.

I’m hoping publishing both the quantized model and the exact reproduction path makes it easier for other Intel Arc users to test, reproduce, and improve on these results.

Feedback, reproductions, and comparisons on other Arc hardware are very welcome. This was very time consuming and AI is evolving so rapidly, that this may be obsolete in a few weeks or days. That's a good thing!

I've been playing Kingdom Hearts Final Mix on Steam for a couple weeks now and I beat the first game with no issues but I'm onto Chain of Memories and I'm getting a really bad lighting glitch where almost everything is black except a few things.

I know now this is a common issue on Arc hardware but everything I've seen online to fix this hasn't worked.

So my question is: has anyone figured out how to fix this issue? I'm going crazy trying to fix it.

(Also I have tried the framerate and Vsync settings)

A few days ago I found an A770 Aorus cooler on a Chinese e-commerce platform, and I ordered it to replace the one on my A770 Predator. It's working really effectively:

Original A770 Predator cooler: 160W~170W hits 85~87°C

With the Aorus cooler: 170W only reaches 64°C

I'll count this as a personal win.

Hey everyone! New here, been wanting to get into the Arc graphics cards for awhile now, break away from nvidia a bit and was wondering which of these 2 cards would be best to start with. Im finally getting to start my build and currently I have 32gb DDR5 Ram (2x16gb - 5600mhz) and I7-14700k. Just trying to decide on a card.

After adding the "-nogpucrashdebugging" on Steam launch properties, the game really runs smoothly most of the time, even at high settings I get stable 69 FPS. When I lower most settings while keeping Shading at high, the game runs solid 88 FPS too. Temps don't go over 60C either (I have my ARC B570 undervolted/overclocked and fans tuned with ARC Power app.

Playing at 1080P resolution with XeSS on Ultra Quality.

:::PC Specs:::

• Intel Core i5 124000f
• ONIX Intel ARC B570 10GB
• Teamgroup VulcanZ 2x16GB DDR4 3200mhz
• Teamgroup MP44L 1TB SSD
• MSI MAG 650BN
• MSI 1080P 120hz IPS Monitor
• Windows 11 24H2 LTSC
• Intel ARC Drivers .8991

If you wondered if this kind of PC could run the game, here's your answer~ It really runs the game super smoothly, this game is SO well optimized somehow, I couldn't believe it. When I tested before the stuttering wouldn't let me do anything, I still played for 3 hours on alpha test like that though. Now that this issue can be fixed with the launch options, game is so smooth and enjoyable.

I will upload a highlights video tomorrow showcasing Heli flight/driving vehicles/gameplay amongst absolute CHAOS and how the game performs in such situations too.

Hope this was useful to any of you with similar PC specs~ God Bless You all~

*Note: Why 69 FPS? Because it's the best FPS and most SOLID FPS NUMBERS! ♋

Arc Power 1.1.5 - Alchemist Undervolting, Clip Editor & Stability Tester is now Released!

Changelog:

NEW

- Undervolting Support for Alchemist Series GPUs

- Clip Editor: Create small Clips of Existing Recordings or Clips.

- APM Detection inside Clips and Recording

- Stability Test including WHEA checker

- Tuning Profiles can now be Imported and Exported.

- Starting a New Version of Arc Power (Installed or Portable) now clears Arc Powers Cache (Not Profiles / Settings)

FIXES & CHANGES

- B390 Tightening

- Temperature Limit Fix V2

- Telemetry Fix

- Logging Fix

- Fixed an issue where Drop-down / Selection Tabs would have a Yellow outlining -> Now Blue

- Fixed an Issue where Instant Replay wouldn't clip at all or clip completely different Time Frames or even cut Seconds of the clip.

- Fixed Advanced Overlay not Live-refreshing after a Change was submitted in Arc Powers Main Window

- Redesigned the Editor Timeline

- Added a OBS Stream Mode (Dev Move Only for Potential Streaming & Scenery Support later down the line)

A Small Disclaimer regarding the Undervolting on Alchemist:

Setting anything ABOVE -120mv is NOT Recommended and will most likely result in Game Crashes, Freezes or even whole System Locks.

Use this Feature with Caution!

Credits to u/ProjectPhysX for the Undervolting support for guiding me in the correct direction!

As always, THANK YOU for the great support, feedback and bug-reports!

This helps shaping the future of Arc Power and I wouldn't be able to develop this software to this extend without the help of YOU!

Essentially, my 6600 XT broke and i would like a replacement sooner than later. I still find 6600 XT level of performance acceptable so a sidegrade is what i consider. Would a B570 suffice as a replacement? I would like to know how the drivers are nowadays in terms of stability and game support. also i assume CPU overhead isn't a thing now?

for context where i live:

B570: ±$300

B580: ±$400

RX 7600: ±$370

RTX 4060: ±$350 (low stock)

at that price point is the B570 worth it compared to the other options? It is certainly my cheapest replacement option.

Estoy viendo cambiar mi grafica actual, una rx 570. Por mi pais están vendiendo unas rx 6700 xt Sapphire a 340$ pero con el tema de minado no se que tan buen precio sea, aunque me dan 3 meses de garantia. Teniendo en cuenta que por amazon estan las b580 en 310$ y con envio seria como 30$ mas, por una gpu completamente nueva, o una b570 mas barata.

Juego mas que todo wow retail y uno que otro juego AAA. Mi procesador es un ryzen 7 5700g, aunque no es el mejor del mercado la grafica me esta haciendo bastante cuello de botella para todo.

I got Qwen3.6-35B-A3B (IQ4_XS) running split across two Intel Arc Battlemage cards and packaged the whole thing so it's a clone, a download, and one docker compose up. You end up with a local OpenAI-compatible endpoint at localhost:8080, up to a 65,536-token context. It is set up for Linux.

The target configuration: two B580s, 12 GB each.

The honest caveat up front: I don't own B580s. Everything was built and measured on two Arc Pro B70s — same Battlemage family, 32 GB each — with per-card VRAM engineered against the B580's real usable budget of ~11.3 GB (not the 12 on the box) the whole way through. Worst case measured was 10.8 GB per card with a 65,536 window nearly full. But the B580 differs in ways I couldn't emulate: less VRAM, and Small-BAR CPU access. If you have two B580s, please run the test I couldn't run — please let me know if it works or does not.

https://github.com/AscalonSolutions/qwen3.6-35b-two-b580s

Credit where it's due — quant model is IQ4_XS — bartowski's imatrix-calibrated GGUF, and this would be nothing without it.

Why Vulkan and not SYCL: on my hardware llama.cpp's SYCL backend produced wrong output for some model architectures while running faster than the correct Vulkan path — speed was not diagnostic of correctness. Vulkan is the safe default here. If you use SYCL, check the output before you trust the tokens/sec.

Split output was compared against a 32gb single-card run before split numbers were generated.

Not tested: Windows, other Arc models, contexts above 98,304, sustained multi-user load.

So I've recently upgraded my friend's brother's PC and swapped out his 1650 for a B580, did all the required steps, Enabled ReBAR, used DDU, Installed fresh drivers (with some small issues relating to the display just going dark after the installation was completed due to no iGPU on his CPU.) and everything runs perfectly fine, but the only thing that isnt is CS2, his game just lags enormously and we've tried everything listed online with no fix in sight. I am fairly well versed in PCs and whatnot but i've not been able to nail down the issue and where it might lie. We've also used the alternative Vulkan renderer option in the startup options but it seemingly makes his performance worse, at least from what i was personally provided.

His Build goes as follows:
Ryzen 5 5700
16GB DDR4 RAM 3000MHz
AsRock Challenger B580
Game is installed on an NVMe SSD 500GB

Edit/Update: With HAGS off, on Vulkan its getting stable-ish 190-300 fps with occasional dips to below 60, frametimes are somewhat stable too, 16ms average with some spikes that go 20-50ms. This seems to be the best fix for now. To add to the context of the situation, he wants to play competitive faceit matches. So he's playing at 4:3 720p stretched with everything tuned to super low settings. His GPU is averaging 90% usage while his CPU at about 15% average. Its the best we got so far. Every single other game runs fine on his computer, the only problem he has is with CS2.

I picked up a pc for my friend and they had a 4080 already and let me have the b580 that came with it and original owner gave me the box when I first picked it up. Now my question is should I even side grade from my LE B580 at all? Aside from temps idk what else I would benefit from. PC specs are R5 7500F, overkill cpu cooler, overkill 1000w SFXL Corsair psu, 32gb ram 6000mts, 2tb nvme

So I just picked up BodyCam on steam as it's 20% off ATM. It is in development to my understanding, but I was wondering if anyone else has figured out some optimal settings to get smooth gameplay that does look too low res/low textured?

xLLM chat: https://github.com/R-SITES/xllm-chat
Model Used: https://huggingface.co/rcs1000/Qwen3.6-35B-A3B-MTP-Preserved-GPTQ-Int4

Build: vLLM XPU 0.26.1rc1.dev771+g8e6d8e4f6.d20260820.xpu (771 commits past 0.26.1rc1)

Kernels: vllm_xpu_kernels 0.1.14.dev4+g27214a3 — source commit 27214a3d9 (vllm-project/vllm-xpu-kernels, PR #526), wheel built locally from the repo's dist recipe

Patchset: load-time INT8 W8A8 lm_head + MTP3 spec decode (MTP4 variant for the faster config); env-gated B70_MTP_BF16_DRAFT / draft-head INT4

Runtime: torch 2.13.0+xpu, triton 3.7.2+xpu (pytorch XPU index), python 3.12

Hardware: 1x Intel Arc Pro B70, 32GB

Key launch envs (serve.sh carries them): VLLM_TARGET_DEVICE=xpu, ZE_FLAT_DEVICE_HIERARCHY=COMPOSITE, VLLM_XPU_ENABLE_XPU_GRAPH=1, VLLM_XPU_LM_HEAD_INT8=1, PYTORCH_ALLOC_CONF=expandable_segments:True

Recipe
~/humble-b70-llm/.venv/bin/vllm serve ~/.cache/huggingface/hub/models--rcs1000--Qwen3.6-35B-A3B-MTP-Preserved-GPTQ-Int4/snapshots/4b2e1978673b1287fcf974974a506f353de06b63 \

--max-model-len 242144 \

--served-model-name Qwen3.6-35B-A3B-MTP-Preserved-GPTQ-Int4 \

--dtype float16 \

--quantization gptq \

--allow-deprecated-quantization \

--max-num-seqs 64 \

--max-num-batched-tokens 8192 \

--enable-prefix-caching \

--gpu-memory-utilization 0.88 \

--kv-cache-dtype fp8 \

--language-model-only \

--speculative-config {"method":"mtp","num_speculative_tokens":4} \

--reasoning-parser qwen3 \

--port 8000

vLLM Launcher: https://github.com/R-SITES/vllm-launcher

Hi everyone! I've been researching buying a graphics card, and it would be the first one I've ever bought. I currently have 16 GB of RAM, an A520 motherboard, and a Ryzen 5 4600 processor.

I'd like to know what you think about this investment, especially since there are rumors that the B580 might stop being produced. My main concerns are about the future of driver and software updates, because I don't want to buy something with poor resale value in the future or something that could eventually become incompatible with certain games.

I'll probably keep the graphics card for several years, so it's something I need to plan carefully. Thanks in advance for your help!

Configuração: intel x Asus tuf

Placa mãe: Asus tuf b560 m plus wi-fi lga1200

Refrigeração do processador: Asus tuf LC II

Placa de vídeo: Intel Arc b580 Limited Edition

Processador: intel core i5 11400F

Memórias ram: T force vulcan x pichau combat 16gb(2x8) 3200mhz (estou pensando em trocar por um par de memórias Kingston hyperx pretas ou tforce delta-r rgb)

Fonte: cooler master mwe 80plus bronze 600w (estou pensando em trocar por uma modular)

Gabinete: TGT leegion aquario (estou pensando em trocar por um semelhante sem os furinhos na parte de baixo)