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Contributed byMario AlkaQwen (Alibaba)

Qwen3-1.7B

Performance benchmark · measured on 12.11.2026 09:48

Benchmark-IDrun-20261112-092948-c7c09b
Timebench 3 - Kombi (Prefill + Generation)Dense1.7BRuntime: OllamaQuantisierung: Q4_K_M
Generation85,48tok/s
Prefill3.232,41tok/s
Time to First Token815,00ms
Total duration40,73s
Concurrency1parallel
Ranking in the field
6of 65 systems

Performance benchmark · Primary metric: Generation-Speed (tok/s) · 1× concurrent

This run is better than 92 % of all comparable systems.
Generation 85,5 tok/s
+197 % vs Ø 28,8
Prefill 3.232,4 tok/s
+248 % vs Ø 928,1
Time to First Token 815 ms
-98 % vs Ø 51.273
Distribution in the field1 – 256 tok/s
Ø 29 Median Dieser Lauf

Wie schlägt sich dieser Benchmark mit anderen Modellen?

How does this benchmark compare on other GPUs?

Same model on different hardware · 1× concurrent · Generation (tok/s)

Hardware

GPU: Keine GPU (CPU-only)
CPU: Apple M6 (unified CPU/GPU SoC)
RAM: 24 GB
Mainboard: Apple Mac mini

Setup

Runtime: Ollama
Quantization: Q4_K_M
Model: Qwen3-1.7B

Configuration

benchmark-konfiguration — run-20261112-092948-c7c09b
# LLM-Benchmark Konfiguration # Modell : Qwen3-1.7B # Engine : Ollama # Run-ID : run-20261112-092948-c7c09b # GPU : Keine GPU (CPU-only) # CPU : Apple M6 (unified CPU/GPU SoC) # RAM : 24 GB bench@llm-benchmark:~$ ollama serve \ --model qwen3:1.7b
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.ollama
Kontextlaenge?Maximale Anzahl Tokens (Eingabe + erzeugte Ausgabe zusammen), die das Modell pro Anfrage verarbeiten kann.8192
execution_typelocal

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Model comparison

Qwen3-1.7B 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

6234683121560,006.75013.49920.249Prefill (tok/s)Generation (tok/s)AMD Radeon AI PRO R9700 - 492,7 tok/s Generation, 14.046 tok/s Prefill, TTFT 873 ms (3 Laufe)AMD Radeon AI PRO R97...AMD Radeon RX 7900 XTX - 445,2 tok/s Generation, 16.451 tok/s Prefill, TTFT 968 ms (9 Laufe)AMD Radeon RX 7900 XTXAMD Oberon (PlayStation 5) - 202,4 tok/s Generation, 1.591 tok/s Prefill, TTFT 4.381 ms (2 Laufe)AMD Oberon (PlayStati...CPU-only - 85,5 tok/s Generation, 840 tok/s Prefill, TTFT 179.696 ms (4 Laufe) | DIESER LAUF★ CPU-only
AMD Radeon AI PRO R9700 492,7 tok/sAMD Radeon RX 7900 XTX 445,2 tok/sAMD Oberon (PlayStation 5) 202,4 tok/s★ CPU-only 85,5 tok/s this run

CPUby processor

6404803201600,007.76015.52123.281Prefill (tok/s)Generation (tok/s)AMD Ryzen 3 3100 4-Core Processor - 492,7 tok/s Generation, 14.046 tok/s Prefill, TTFT 873 ms (3 Laufe)AMD Ryzen 3 3100 4-Co...AMD Ryzen Threadripper PRO 3955WX 16-Cores - 445,2 tok/s Generation, 18.781 tok/s Prefill, TTFT 935 ms (6 Laufe)AMD Ryzen Threadrippe...Intel(R) Xeon(R) CPU E5-4657L v2 @ 2.40GHz - 437,4 tok/s Generation, 11.792 tok/s Prefill, TTFT 1.033 ms (3 Laufe)Intel(R) Xeon(R) CPU ...AMD Zen2 8-Core (PlayStation 5) - 202,4 tok/s Generation, 1.591 tok/s Prefill, TTFT 4.381 ms (2 Laufe)AMD Zen2 8-Core (Play...4 x Cortex-A78C + 4 x Cortex-A55 - 4,0 tok/s Generation, 43 tok/s Prefill, TTFT 239.322 ms (3 Laufe)4 x Cortex-A78C + 4 x...Apple M6 (unified CPU/GPU SoC) - 85,5 tok/s Generation, 3.232 tok/s Prefill, TTFT 815 ms (1 Lauf) | DIESER LAUF★ Apple M6 (unified CPU...
AMD Ryzen 3 3100 4-Core Processor 492,7 tok/sAMD Ryzen Threadripper PRO 3955WX 16-Cores 445,2 tok/sIntel(R) Xeon(R) CPU E5-4657L v2 @ 2.40GHz 437,4 tok/sAMD Zen2 8-Core (PlayStation 5) 202,4 tok/s★ Apple M6 (unified CPU/GPU SoC) 85,5 tok/s this run4 x Cortex-A78C + 4 x Cortex-A55 4,0 tok/s

MBby mainboard

6234683121560,007.72315.44623.170Prefill (tok/s)Generation (tok/s)ASUSTeK COMPUTER INC. ROG STRIX X570-F GAMING - 492,7 tok/s Generation, 14.046 tok/s Prefill, TTFT 873 ms (3 Laufe)ASUSTeK COMPUTER INC....ASUSTeK COMPUTER INC. Pro WS WRX80E-SAGE SE WIFI - 445,2 tok/s Generation, 18.781 tok/s Prefill, TTFT 935 ms (6 Laufe)ASUSTeK COMPUTER INC....Dell Inc. PowerEdge R820 - 437,4 tok/s Generation, 11.792 tok/s Prefill, TTFT 1.033 ms (3 Laufe)Dell Inc. PowerEdge R...unbekannt - 202,4 tok/s Generation, 662 tok/s Prefill, TTFT 145.346 ms (5 Laufe)unbekanntApple Mac mini - 85,5 tok/s Generation, 3.232 tok/s Prefill, TTFT 815 ms (1 Lauf) | DIESER LAUF★ Apple Mac mini
ASUSTeK COMPUTER INC. ROG STRIX X570-F GAMING 492,7 tok/sASUSTeK COMPUTER INC. Pro WS WRX80E-SAGE SE WIFI 445,2 tok/sDell Inc. PowerEdge R820 437,4 tok/sunbekannt 202,4 tok/s★ Apple Mac mini 85,5 tok/s this run

ENGby engine

6234683121560,009.42718.85428.281Prefill (tok/s)Generation (tok/s)llama.cpp - 492,7 tok/s Generation, 8.834 tok/s Prefill, TTFT 52.499 ms (14 Laufe)llama.cppvLLM - 387,7 tok/s Generation, 23.277 tok/s Prefill, TTFT 1.026 ms (3 Laufe)vLLMOllama - 85,5 tok/s Generation, 3.232 tok/s Prefill, TTFT 815 ms (1 Lauf) | DIESER LAUF★ Ollama
llama.cpp 492,7 tok/svLLM 387,7 tok/s★ Ollama 85,5 tok/s this run

DRVby driver

54251749346844310.27410.71111.14911.586Prefill (tok/s)Generation (tok/s)unbekannt - 492,7 tok/s Generation, 10.930 tok/s Prefill, TTFT 41.048 ms (18 Laufe)unbekannt
unbekannt 492,7 tok/s
💰 Economics

Economics of this run

Operating cost, TCO and comparison with the next-best runs of the same model at identical concurrency (1× 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 %
🔌 Idle 0 W
⚡ TDP 10 W
☁️ External LLM (API)
Electricity0.30 EUR/kWh
Avg power (incl. idle)0 W missing
Avg cost / hour–
Electricity / 1M tokens–
Token / kWh–
Acquisition (system)– partial price
Electricity (2 years)–
TCO (2 years)–
Output tokens (2 years)5.39B
☁️ External LLM (API) – comparison
External LLM cost (2 years)–
Savings vs. external (2 years)–
No power draw measured – values estimated from GPU TDP + CPU (idle + 15 %) + board.

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 (0 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

Qwen3-1.7BKeine GPU (CPU-only)Qwen3-1.7BAMD Oberon (PlayStation 5)Qwen3-1.7BAMD Radeon AI PRO R9700Qwen3-1.7B2x AMD Radeon RX 7900 XTX
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.