Gemma 2 9B IT vs GPT OSS 20B
GPT OSS 20B leads llmrun Score 96.4 to 68.0; both fit 24 GB at Q4_K_M; GPT OSS 20B is 1.8× faster on RTX 4090 (~190 vs ~107 tok/s).
Model B · OpenAI
GPT OSS 20B20.9B · 4.2B active · 128K context · Apache 2.0 · Aug 2025
Choose Gemma 2 9B IT if you want…
Fits an 8 GB GPU
Q4_K_M · 7.3 GB; GPT OSS 20B needs 6.3 GB at its smallest quant
Lighter on memory
6.1 vs 12.9 GB at Q4_K_M
Choose GPT OSS 20B if you want…
Higher llmrun Score
96.4 vs 68.0
Ahead on the benchmarks
3 of 3 shared boards
1.8× faster on RTX 4090
~190 vs ~107 tok/s
Longer context window
128K vs 8K tokens
Also does function-calling
Gemma 2 9B IT doesn't list it
More permissive license
Apache 2.0 vs Gemma Terms
On your hardware
Each model at its default quant (Q4_K_M), a smaller one when it must. Estimates, ±20%.
8 GB
RTX 4060 · 8 GB tier
Gemma 2 9B IT
Q4_K_M · ~29 tok/s
7.3 GB · up to 8Kmore headroom
GPT OSS 20B
IQ2_M · ~103 tok/s
7.6 GB · up to 32K
12 GB
RTX 3060 12GB · 12 GB tier
Gemma 2 9B IT
Q4_K_M · ~38 tok/s
7.3 GB · up to 8Kmore headroom
GPT OSS 20B
IQ4_XS · ~89 tok/s
11.8 GB · up to 16K
16 GB
RTX 5060 Ti 16GB · 16 GB tier
Gemma 2 9B IT
Q4_K_M · ~48 tok/s
7.3 GB · up to 8K
GPT OSS 20B
Q4_K_M · ~98 tok/s
13.1 GB · up to 128Kfaster
24 GBreference
RTX 4090 · 24 GB tier
Gemma 2 9B IT
Q4_K_M · ~107 tok/s
7.3 GB · up to 8K
GPT OSS 20B
Q4_K_M · ~190 tok/s
13.1 GB · up to 128Kfaster
32 GB
RTX 5090 · 32 GB tier
Gemma 2 9B IT
Q4_K_M · ~191 tok/s
7.3 GB · up to 8K
GPT OSS 20B
Q4_K_M · ~282 tok/s
13.1 GB · up to 128Kfaster
48 GB
RTX A6000 · 48 GB tier
Gemma 2 9B IT
Q4_K_M · ~82 tok/s
7.3 GB · up to 8K
GPT OSS 20B
Q4_K_M · ~154 tok/s
13.1 GB · up to 128Kfaster
Mac 32 GB
Mac Mini M4 · Macs
Gemma 2 9B IT
Q4_K_M · ~14 tok/s
7.3 GB · up to 8K
GPT OSS 20B
Q4_K_M · ~28 tok/s
13.1 GB · up to 128Kfaster
Mac 64 GB
Mac Studio M4 Max · Macs
Gemma 2 9B IT
Q4_K_M · ~63 tok/s
7.3 GB · up to 8K
GPT OSS 20B
Q4_K_M · ~86 tok/s
13.1 GB · up to 128Kfaster
Mac 128 GB
Mac Studio M4 Max · Macs
Gemma 2 9B IT
Q4_K_M · ~63 tok/s
7.3 GB · up to 8K
GPT OSS 20B
Q4_K_M · ~86 tok/s
13.1 GB · up to 128Kfaster
Reference GPU: RTX 4090. Tinted cell = the better pick on that machine (fits, more headroom, or at least 10% faster).
Overall
Gemma 2 9B IT
GPT OSS 20B
Coding
Gemma 2 9B IT
no data
GPT OSS 20B
Science
Gemma 2 9B IT
no data
GPT OSS 20B
Reasoning
Gemma 2 9B IT
no data
GPT OSS 20B
Gemma 2 9B IT · #99 of 106 open models · #30 of 36 that fit 24 GB
GPT OSS 20B · #69 of 106 open models · #16 of 36 that fit 24 GB
Benchmarks
3 shared boards: Gemma 2 9B IT leads 0, GPT OSS 20B leads 3 · Benchmarks imported Nov 2026
Gemma 2 9B IT
27.5%#88/100 open
IndependentEpoch AI · Jun 2024
GPT OSS 20B
60.8%#44/100 open
IndependentEpoch AI · Aug 2025
Gemma 2 9B IT
0.6%#84/88 open
IndependentEpoch AI · Jun 2024
GPT OSS 20B
65.3%#36/88 open
IndependentEpoch AI · Aug 2025
Gemma 2 9B IT
52.1%#73/146 open
IndependentTIGER-Lab
GPT OSS 20B
73.6%#33/146 open
IndependentTIGER-Lab
10 more boards (other shared and single-model boards)
Gemma 2 9B IT
1267.0#125/188 open
ArenaLMArena · Oct 2026
GPT OSS 20B
1317.3#98/188 open
ArenaLMArena · Oct 2026
Only Gemma 2 9B IT (2)
- MATH Level 521.0%
- MMLU72.1%
VRAM by quantization
Memory to load the model and 2K context; below it, the total at 32K and 128K context. Lighter side in bold.
Q2_K
Gemma 2 9B IT
4.3 GB3.8 GB file
32K — · 128K —
GPT OSS 20B
9.3 GB11.5 GB file
32K 9.8 GB · 128K 11.5 GB
Q3_K_S
Gemma 2 9B IT
4.5 GB4.3 GB file
32K — · 128K —
GPT OSS 20B
9.5 GB11.5 GB file
32K 10.0 GB · 128K 11.7 GB
Q3_K_M
Gemma 2 9B IT
5.0 GB4.8 GB file
32K — · 128K —
GPT OSS 20B
10.6 GB11.5 GB file
32K 11.1 GB · 128K 12.8 GB
Q4_0
Gemma 2 9B IT
5.1 GB5.4 GB file
32K — · 128K —
GPT OSS 20B
10.8 GB11.5 GB file
32K 11.3 GB · 128K 13.0 GB
Q4_K_M
Gemma 2 9B IT
6.1 GB5.8 GB file
32K — · 128K —
GPT OSS 20B
12.9 GB11.6 GB file
32K 13.4 GB · 128K 15.1 GB
Q5_K_M
Gemma 2 9B IT
7.2 GB6.6 GB file
32K — · 128K —
GPT OSS 20B
15.3 GB11.7 GB file
32K 15.8 GB · 128K 17.5 GB
Q6_K
Gemma 2 9B IT
8.4 GB7.6 GB file
32K — · 128K —
GPT OSS 20B
17.6 GB12.0 GB file
32K 18.1 GB · 128K 19.8 GB
Q8_0
Gemma 2 9B IT
10.2 GB9.8 GB file
32K — · 128K —
GPT OSS 20B
21.3 GB~20.9 GB file
32K 21.8 GB · 128K 23.5 GB
20 more quants
IQ2_XXS
Gemma 2 9B IT
2.8 GB2.8 GB file
32K — · 128K —
GPT OSS 20B
6.1 GB~5.8 GB file
32K 6.6 GB · 128K 8.3 GB
IQ2_XS
Gemma 2 9B IT
3.1 GB3.1 GB file
32K — · 128K —
GPT OSS 20B
6.7 GB~6.3 GB file
32K 7.2 GB · 128K 8.9 GB
IQ2_S
Gemma 2 9B IT
3.2 GB3.2 GB file
32K — · 128K —
GPT OSS 20B
6.9 GB~6.5 GB file
32K 7.4 GB · 128K 9.1 GB
IQ2_M
Gemma 2 9B IT
3.4 GB3.4 GB file
32K — · 128K —
GPT OSS 20B
7.4 GB~7.1 GB file
32K 7.9 GB · 128K 9.6 GB
IQ3_XXS
Gemma 2 9B IT
3.9 GB3.8 GB file
32K — · 128K —
GPT OSS 20B
8.5 GB11.6 GB file
32K 9.0 GB · 128K 10.7 GB
Q2_K_S
Gemma 2 9B IT
not listed
GPT OSS 20B
8.7 GB12.1 GB file
32K 9.2 GB · 128K 10.9 GB
IQ3_XS
Gemma 2 9B IT
4.2 GB4.1 GB file
32K — · 128K —
GPT OSS 20B
9.0 GB11.6 GB file
32K 9.5 GB · 128K 11.2 GB
IQ3_S
Gemma 2 9B IT
4.3 GB4.3 GB file
32K — · 128K —
GPT OSS 20B
9.3 GB12.1 GB file
32K 9.8 GB · 128K 11.5 GB
IQ3_M
Gemma 2 9B IT
4.6 GB4.5 GB file
32K — · 128K —
GPT OSS 20B
9.8 GB11.6 GB file
32K 10.3 GB · 128K 12.0 GB
Q3_K_L
Gemma 2 9B IT
5.2 GB5.1 GB file
32K — · 128K —
GPT OSS 20B
11.1 GB11.5 GB file
32K 11.6 GB · 128K 13.3 GB
IQ4_XS
Gemma 2 9B IT
5.5 GB5.2 GB file
32K — · 128K —
GPT OSS 20B
11.6 GB11.6 GB file
32K 12.1 GB · 128K 13.8 GB
IQ4_NL
Gemma 2 9B IT
not listed
GPT OSS 20B
12.1 GB11.6 GB file
32K 12.6 GB · 128K 14.3 GB
Q4_1
Gemma 2 9B IT
5.7 GB6.0 GB file
32K — · 128K —
GPT OSS 20B
12.1 GB11.6 GB file
32K 12.6 GB · 128K 14.3 GB
Q4_K_S
Gemma 2 9B IT
5.7 GB5.5 GB file
32K — · 128K —
GPT OSS 20B
12.1 GB11.6 GB file
32K 12.6 GB · 128K 14.3 GB
Q4_K_L
Gemma 2 9B IT
6.2 GB6.0 GB file
32K — · 128K —
GPT OSS 20B
13.2 GB11.9 GB file
32K 13.7 GB · 128K 15.4 GB
Q5_0
Gemma 2 9B IT
6.4 GB6.5 GB file
32K — · 128K —
GPT OSS 20B
not listed
Q5_1
Gemma 2 9B IT
7.0 GB7.0 GB file
32K — · 128K —
GPT OSS 20B
not listed
Q5_K_S
Gemma 2 9B IT
7.0 GB6.5 GB file
32K — · 128K —
GPT OSS 20B
14.8 GB11.7 GB file
32K 15.3 GB · 128K 17.0 GB
Q5_K_L
Gemma 2 9B IT
7.4 GB6.9 GB file
32K — · 128K —
GPT OSS 20B
15.5 GB11.9 GB file
32K 16.0 GB · 128K 17.7 GB
BF16
Gemma 2 9B IT
20.3 GB18.5 GB file
32K — · 128K —
GPT OSS 20B
42.2 GB~41.8 GB file
32K 42.7 GB · 128K 44.4 GB
Gemma 2 9B IT
Ollama · Q4_K_M
ollama run hf.co/bartowski/gemma-2-9b-it-GGUF:Q4_K_MGPT OSS 20B
Ollama · Q4_K_M
ollama run hf.co/unsloth/gpt-oss-20b-GGUF:Q4_K_M| Spec | Gemma 2 9B IT | GPT OSS 20B |
|---|---|---|
| Publisher | OpenAI | |
| Parameters | 9.2B | 20.9B |
| Active parameters | — | 4.2B per token |
| Architecture | — | GptOssForCausalLM |
| Context | 8K tokens | 128K tokens |
| Modalities | Chat | Chat, Function-calling |
| License | Gemma Terms | Apache 2.0 |
| Released | Jun 2024 | Aug 2025 |
Frequently Asked Questions
Which is better, Gemma 2 9B IT or GPT OSS 20B?
GPT OSS 20B leads llmrun Score 96.4 to 68.0; both fit 24 GB at Q4_K_M; GPT OSS 20B is 1.8× faster on RTX 4090 (~190 vs ~107 tok/s). Choose Gemma 2 9B IT for fits an 8 GB GPU and lighter on memory; choose GPT OSS 20B for higher llmrun Score and ahead on the benchmarks.
Which needs less VRAM, Gemma 2 9B IT or GPT OSS 20B?
At Q4_K_M, Gemma 2 9B IT requires 6.1 GB while GPT OSS 20B needs 12.9 GB, making Gemma 2 9B IT the easier model to run on your local setup.
Which is faster on RTX 4090?
Estimated decode speed on RTX 4090 is about 107 tok/s for Gemma 2 9B IT (Q4_K_M) and 190 tok/s for GPT OSS 20B (Q4_K_M), so GPT OSS 20B is faster. Estimates, ±20%.
Can I run Gemma 2 9B IT or GPT OSS 20B on a 16 GB GPU?
Gemma 2 9B IT fits at Q4_K_M; GPT OSS 20B fits at Q4_K_M.
Which has a longer context window, Gemma 2 9B IT or GPT OSS 20B?
Gemma 2 9B IT supports 8,192 tokens and GPT OSS 20B supports 131,072 tokens.