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Contributed byMario AlkaCohere

North-Mini-Code-1.0

Performance benchmark · measured on 22.07.2026 20:37

Benchmark-IDrun-20260723-015518-753958
Timebench 3 - Kombi (Prefill + Generation)Runtime: llama.cppQuantisierung: Q4_K_M
For context: Diese Plattform nutzt Unified Memory – die "VRAM" ist gemeinsamer System-RAM (APU/Superchip); das Modell teilt sich den Speicher mit dem System.
Generation131,91tok/s
Prefill1.758,99tok/s
Time to First Token13.043,00ms
Total duration72,76s
Concurrency10parallel
Ranking in the field
1of 12 systems

Performance benchmark · Primary metric: Generation-Speed (tok/s) · 10× concurrent

This run is better than 100 % of all comparable systems.
Generation 131,9 tok/s
+80 % vs Ø 73,5
Prefill 1.759,0 tok/s
+40 % vs Ø 1.253,9
Time to First Token 13.043 ms
-42 % vs Ø 22.577
Distribution in the field17 – 132 tok/s
Ø 73 Median Dieser Lauf

Wie schlägt sich dieser Benchmark mit anderen Modellen?

How does this benchmark compare on other GPUs?

Same model on different hardware · 10× concurrent · Generation (tok/s)

Hardware

GPU: AMD Radeon 8060S Graphics
CPU: AMD RYZEN AI MAX+ 395 w/ Radeon 8060S
RAM: 31 GB
Mainboard: Bosgame AXB35-02 (BeyondMax Series)

Setup

Runtime: llama.cpp
Quantization: Q4_K_M
Model: North-Mini-Code-1.0

Configuration

benchmark-konfiguration — run-20260723-015518-753958
# LLM-Benchmark Konfiguration # Modell : North-Mini-Code-1.0 # Engine : llama.cpp # Run-ID : run-20260723-015518-753958 # GPU : AMD Radeon 8060S Graphics # CPU : AMD RYZEN AI MAX+ 395 w/ Radeon 8060S # RAM : 31 GB bench@llm-benchmark:~$ /home/godcore/llama.cpp/build-rocm/bin/llama-server \ -m /home/godcore/models/dl/North-Mini-Code-1.0-UD-Q4_K_M.gguf \ --host 0.0.0.0 \ --port 8000 \ --gpu-layers 99 \ --flash-attn on \ -c 26624 \ --parallel 12
Engine?Die Inferenz-Software, die das Modell ausliefert (z.B. vLLM oder llama.cpp). Sie bestimmt Geschwindigkeit, unterstuetzte Modellformate und welche Parameter ueberhaupt verfuegbar sind.llamacpp
Kontextlaenge?Maximale Anzahl Tokens (Eingabe + erzeugte Ausgabe zusammen), die das Modell pro Anfrage verarbeiten kann.26624
Modellpfad?Pfad zur GGUF-Modelldatei, die geladen und ausgeliefert wird./home/godcore/models/dl/North-Mini-Code-1.0-UD-Q4_K_M.gguf
GPU-Layer?Anzahl der auf die GPU ausgelagerten Modell-Layer. Hoeher = mehr VRAM und schneller; der Rest laeuft auf der CPU. 999 = alles auf GPU.99
Flash Attention?FlashAttention fuer schnellere und speichersparende Attention. Wert on/off/auto je nach Build.on
Kontext?Groesse des Kontextfensters in Token. 0 = der beim Training verwendete Kontext des Modells.26624
Parallel?Anzahl paralleler Slots/Sequenzen, die der Server gleichzeitig bedient. Der Kontext wird auf die Slots aufgeteilt.12

All benchmarks of this model To leaderboard

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Model comparison

North-Mini-Code-1.0 on various hardware

All published performance runs of this model – each bubble a variant: position = prefill (X) × generation (Y), bubble size = number of runs. Closer to the top right = faster. ★ Marked gold = this benchmark.

GPUby graphics card

2.1061.5801.0535270,005.85511.71017.566Prefill (tok/s)Generation (tok/s)NVIDIA RTX PRO 6000 Blackwell Workstation Edition - 1.621,0 tok/s Generation, 6.099 tok/s Prefill, TTFT 3.593 ms (3 Laufe)NVIDIA RTX PRO 6000 B...NVIDIA GeForce RTX 5090 - 1.557,3 tok/s Generation, 5.892 tok/s Prefill, TTFT 3.954 ms (3 Laufe)NVIDIA GeForce RTX 50...NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition - 1.492,4 tok/s Generation, 8.535 tok/s Prefill, TTFT 3.497 ms (12 Laufe)NVIDIA RTX PRO 6000 B...NVIDIA GeForce RTX 3090 Ti - 939,5 tok/s Generation, 4.130 tok/s Prefill, TTFT 5.948 ms (3 Laufe)NVIDIA GeForce RTX 30...NVIDIA RTX A6000 - 648,5 tok/s Generation, 14.179 tok/s Prefill, TTFT 1.659 ms (30 Laufe)NVIDIA RTX A6000AMD Radeon PRO W7800 48GB - 276,9 tok/s Generation, 2.774 tok/s Prefill, TTFT 3.679 ms (6 Laufe)AMD Radeon PRO W7800 ...NVIDIA GeForce RTX 5070 Ti - 169,0 tok/s Generation, 890 tok/s Prefill, TTFT 31.856 ms (3 Laufe)NVIDIA GeForce RTX 50...AMD Radeon AI PRO R9700 - 87,3 tok/s Generation, 502 tok/s Prefill, TTFT 82.917 ms (10 Laufe)AMD Radeon AI PRO R97...NVIDIA GeForce RTX 2060 - 5,1 tok/s Generation, 89 tok/s Prefill, TTFT 113.797 ms (3 Laufe)NVIDIA GeForce RTX 20...AMD Radeon 8060S Graphics - 131,9 tok/s Generation, 1.759 tok/s Prefill, TTFT 13.043 ms (1 Lauf) | DIESER LAUF★ AMD Radeon 8060S Grap...
NVIDIA RTX PRO 6000 Blackwell Workstation Edition 1.621,0 tok/sNVIDIA GeForce RTX 5090 1.557,3 tok/sNVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition 1.492,4 tok/sNVIDIA GeForce RTX 3090 Ti 939,5 tok/sNVIDIA RTX A6000 648,5 tok/sAMD Radeon PRO W7800 48GB 276,9 tok/sNVIDIA GeForce RTX 5070 Ti 169,0 tok/s★ AMD Radeon 8060S Graphics 131,9 tok/s this runAMD Radeon AI PRO R9700 87,3 tok/sNVIDIA GeForce RTX 2060 5,1 tok/s

CPUby processor

2.1061.5801.0535270,004.4428.88413.326Prefill (tok/s)Generation (tok/s)AMD Ryzen 9 9950X 16-Core Processor - 1.621,0 tok/s Generation, 6.099 tok/s Prefill, TTFT 3.593 ms (3 Laufe)AMD Ryzen 9 9950X 16-...AMD Ryzen 7 5800X3D 8-Core Processor - 1.557,3 tok/s Generation, 5.892 tok/s Prefill, TTFT 3.954 ms (3 Laufe)AMD Ryzen 7 5800X3D 8...AMD Ryzen Threadripper PRO 9965WX 24-Cores - 1.492,4 tok/s Generation, 8.535 tok/s Prefill, TTFT 3.497 ms (12 Laufe)AMD Ryzen Threadrippe...AMD Ryzen 9 8945HX with Radeon Graphics - 939,5 tok/s Generation, 4.130 tok/s Prefill, TTFT 5.948 ms (3 Laufe)AMD Ryzen 9 8945HX wi...AMD Ryzen Threadripper PRO 7955WX 16-Cores - 648,5 tok/s Generation, 10.760 tok/s Prefill, TTFT 21.973 ms (40 Laufe)AMD Ryzen Threadrippe...AMD Ryzen Threadripper PRO 5975WX 32-Cores - 276,9 tok/s Generation, 2.146 tok/s Prefill, TTFT 13.071 ms (9 Laufe)AMD Ryzen Threadrippe...Intel(R) Xeon(R) CPU E5-4620 v2 @ 2.60GHz - 5,1 tok/s Generation, 89 tok/s Prefill, TTFT 113.797 ms (3 Laufe)Intel(R) Xeon(R) CPU ...AMD RYZEN AI MAX+ 395 w/ Radeon 8060S - 131,9 tok/s Generation, 1.759 tok/s Prefill, TTFT 13.043 ms (1 Lauf) | DIESER LAUF★ AMD RYZEN AI MAX+ 395...
AMD Ryzen 9 9950X 16-Core Processor 1.621,0 tok/sAMD Ryzen 7 5800X3D 8-Core Processor 1.557,3 tok/sAMD Ryzen Threadripper PRO 9965WX 24-Cores 1.492,4 tok/sAMD Ryzen 9 8945HX with Radeon Graphics 939,5 tok/sAMD Ryzen Threadripper PRO 7955WX 16-Cores 648,5 tok/sAMD Ryzen Threadripper PRO 5975WX 32-Cores 276,9 tok/s★ AMD RYZEN AI MAX+ 395 w/ Radeon 8060S 131,9 tok/s this runIntel(R) Xeon(R) CPU E5-4620 v2 @ 2.60GHz 5,1 tok/s

MBby mainboard

2.1061.5801.0535270,004.2308.46012.689Prefill (tok/s)Generation (tok/s)ASUSTeK COMPUTER INC. ProArt X870E-CREATOR WIFI - 1.621,0 tok/s Generation, 6.099 tok/s Prefill, TTFT 3.593 ms (3 Laufe)ASUSTeK COMPUTER INC....ASUSTeK COMPUTER INC. ROG STRIX B550-A GAMING - 1.557,3 tok/s Generation, 5.892 tok/s Prefill, TTFT 3.954 ms (3 Laufe)ASUSTeK COMPUTER INC....ASUSTeK COMPUTER INC. Pro WS WRX90E-SAGE SE - 1.492,4 tok/s Generation, 10.246 tok/s Prefill, TTFT 17.709 ms (52 Laufe)ASUSTeK COMPUTER INC....Meigao Innovation Technology (Shen Zhen) Co., Ltd DRFXL (MotherBoard Series) - 939,5 tok/s Generation, 4.130 tok/s Prefill, TTFT 5.948 ms (3 Laufe)Meigao Innovation Tec...ASUSTeK COMPUTER INC. Pro WS WRX80E-SAGE SE WIFI - 276,9 tok/s Generation, 2.146 tok/s Prefill, TTFT 13.071 ms (9 Laufe)ASUSTeK COMPUTER INC....Dell Inc. PowerEdge R820 - 5,1 tok/s Generation, 89 tok/s Prefill, TTFT 113.797 ms (3 Laufe)Dell Inc. PowerEdge R...Bosgame AXB35-02 (BeyondMax Series) - 131,9 tok/s Generation, 1.759 tok/s Prefill, TTFT 13.043 ms (1 Lauf) | DIESER LAUF★ Bosgame AXB35-02 (Bey...
ASUSTeK COMPUTER INC. ProArt X870E-CREATOR WIFI 1.621,0 tok/sASUSTeK COMPUTER INC. ROG STRIX B550-A GAMING 1.557,3 tok/sASUSTeK COMPUTER INC. Pro WS WRX90E-SAGE SE 1.492,4 tok/sMeigao Innovation Technology (Shen Zhen) Co., Ltd DRFXL (MotherBoard Series) 939,5 tok/sASUSTeK COMPUTER INC. Pro WS WRX80E-SAGE SE WIFI 276,9 tok/s★ Bosgame AXB35-02 (BeyondMax Series) 131,9 tok/s this runDell Inc. PowerEdge R820 5,1 tok/s

ENGby engine

1.9781.5561.1357132926168.20415.79123.379Prefill (tok/s)Generation (tok/s)vLLM - 648,5 tok/s Generation, 19.505 tok/s Prefill, TTFT 642 ms (18 Laufe)vLLMllama.cpp - 1.621,0 tok/s Generation, 4.489 tok/s Prefill, TTFT 25.391 ms (56 Laufe) | DIESER LAUF★ llama.cpp
★ llama.cpp 1.621,0 tok/s this runvLLM 648,5 tok/s

DRVby driver

1.7831.7021.6211.5401.4597.6537.9798.3058.630Prefill (tok/s)Generation (tok/s)unbekannt - 1.621,0 tok/s Generation, 8.142 tok/s Prefill, TTFT 19.371 ms (74 Laufe)unbekannt
unbekannt 1.621,0 tok/s
💰 Economics

Economics of this run

Operating cost, TCO and comparison with the next-best runs of the same model at identical concurrency (10× concurrent). Methodology →

⚙️ ConfigurationAll metrics and charts below follow these settings – based on a 24-month runtime.Save to URLReset
⚡ Electricity price EUR/kWh
⚙️ System utilization 100 %
🖥️ Acquisition EUR
🔌 Idle 18 W
⚡ TDP 120 W
☁️ External LLM (API)
Electricity0.30 EUR/kWh
Avg power (incl. idle)120 W estimated (TDP)GPU 120 W full load
Avg cost / hourEUR 0.036
Electricity / 1M tokensEUR 0.076
Token / kWh3.96M
Acquisition (system)EUR 7,054 partial priceGPU EUR 3,000 · Board EUR 3,500 · RAM EUR 434 · PSU EUR 120
Electricity (2 years)
TCO (2 years)EUR 7,685
Output tokens (2 years)8.32B
☁️ External LLM (API) – comparison
External LLM cost (2 years)
Savings vs. external (2 years)

All values above and the charts below take the configured system utilization into account: at X% the system generates only X% of the time, the rest it idles (18 W). Cost per hour drops (more idle), cost per token rises.

Cost over 2 years – electricity only

Cost over 2 years – incl. acquisition (TCO)

Speed vs. tokens per euro

Euro per 1M tokens

Comparison vs. API – economics per benchmark

North-Mini-Code-1.0AMD Radeon 8060S GraphicsNorth-Mini-Code-1.0NVIDIA RTX PRO 6000 Blackwell Workstation EditionNorth-Mini-Code-1.0NVIDIA GeForce RTX 5090North-Mini-Code-1.03x NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition
Electricity cost (24 mo.)
Acquisition cost
Total cost (TCO)
Generated tokens (24 mo.)
Token price via API
Break-even point (days)
Result (savings / extra cost)

Comparison with up to 3 next-best runs of this model at the same concurrency (at least one on different hardware). Power = GPU TDP + CPU (idle + 15 %) + board (estimated), acquisition = full system (GPU + CPU + board + RAM + PSU), prices = stored market prices.

Contributed by

Mario Alka Administrator

@marioalka

Ich bin Unternehmer, Softwareentwickler und KI-Enthusiast. Seit vielen Jahren entwickle ich Unternehmenssoftware und beschäftige mich inzwischen fast täglich mit lokalen LLMs, KI-Agenten und leistungsfähiger KI-Hardware.

Mit LLM-Benchmark.de möchte ich eine Plattform schaffen, auf der Modelle, GPUs und Agenten objektiv und reproduzierbar miteinander verglichen werden.