Comparisons / LLaVA-1.5 vs CLIP ViT-B/32

LLaVA-1.5 vs CLIP ViT-B/32

A vision-language model against the encoder it is built on.

CLIP ViT-B/32 has 6.9B fewer parameters than LLaVA-1.5: 7 layers added, 196 removed, 32 changed.

Baseline

LLaVA-1.5

Layers: 226
Parameters: 7.1B
Input: 3 × 336 × 336
Output: 1 × 2624 × 32000
Forward-passes: yes
Est. train cost: $690.06

Compared

CLIP ViT-B/32

Layers: 37
Parameters: 151M
Input: 3 × 224 × 224
Output: 512
Forward-passes: yes
Est. train cost: $0.313

The deltas

Every number is CLIP ViT-B/32 relative to LLaVA-1.5.

Parameters

-6.9B (-97.9%)

Layers

-189

Added

Removed

196

Changed

Unchanged

Which GPUs each one fits

Each side is measured at its own declared input (3 × 336 × 336 against 3 × 224 × 224). Both columns are right about their own model; the difference between them is not a fact about the designs.

GPU	LLaVA-1.5	CLIP ViT-B/32
T4 16GB	no	fits
A100 40GB	no	fits
H100 80GB	no	fits

Layer by layer

Aligned in topological order. 1 of 236 rows are the same layer with the same parameters.

Show all 236 rows

		LLaVA-1.5			CLIP ViT-B/32
		Layer	Params	Output	Layer	Params	Output
1	changed shape	image Input		3 × 336 × 336	image Input		3 × 224 × 224
2	changed shape	text_tokens Input		1 × 2048	tokens Input		77
3	changed imgSize, patchSize, embedDim	clip_patch_14 Patch Embed	603K	576 × 1024	patch_embed Patch Embed	2.4M	49 × 768
4	changed numEmbeddings, embeddingDim	token_embed Embedding	131M	1 × 2048 × 4096	tok_embed Embedding	25M	77 × 512
5	added	—			vis_pos Positional Encoding		49 × 768
6	changed maxLen, embedDim	vis_pos Positional Encoding		576 × 1024	txt_pos Positional Encoding		77 × 512
7	changed embedDim, numHeads, ffDim	clip_block_1 Transformer Block	13M	576 × 1024	vis_block_1 Transformer Block	7.1M	49 × 768
8	changed embedDim, numHeads, ffDim	clip_block_2 Transformer Block	13M	576 × 1024	txt_block_1 Transformer Block	3.2M	77 × 512
9	changed embedDim, numHeads, ffDim	clip_block_3 Transformer Block	13M	576 × 1024	vis_block_2 Transformer Block	7.1M	49 × 768
10	changed embedDim, numHeads, ffDim	clip_block_4 Transformer Block	13M	576 × 1024	txt_block_2 Transformer Block	3.2M	77 × 512
11	changed embedDim, numHeads, ffDim	clip_block_5 Transformer Block	13M	576 × 1024	vis_block_3 Transformer Block	7.1M	49 × 768
12	changed embedDim, numHeads, ffDim	clip_block_6 Transformer Block	13M	576 × 1024	txt_block_3 Transformer Block	3.2M	77 × 512
13	changed embedDim, numHeads, ffDim	clip_block_7 Transformer Block	13M	576 × 1024	vis_block_4 Transformer Block	7.1M	49 × 768
14	changed embedDim, numHeads, ffDim	clip_block_8 Transformer Block	13M	576 × 1024	txt_block_4 Transformer Block	3.2M	77 × 512
15	changed embedDim, numHeads, ffDim	clip_block_9 Transformer Block	13M	576 × 1024	vis_block_5 Transformer Block	7.1M	49 × 768
16	changed embedDim, numHeads, ffDim	clip_block_10 Transformer Block	13M	576 × 1024	txt_block_5 Transformer Block	3.2M	77 × 512
17	changed embedDim, numHeads, ffDim	clip_block_11 Transformer Block	13M	576 × 1024	vis_block_6 Transformer Block	7.1M	49 × 768
18	changed embedDim, numHeads, ffDim	clip_block_12 Transformer Block	13M	576 × 1024	txt_block_6 Transformer Block	3.2M	77 × 512
19	changed embedDim, numHeads, ffDim	clip_block_13 Transformer Block	13M	576 × 1024	vis_block_7 Transformer Block	7.1M	49 × 768
20	changed embedDim, numHeads, ffDim	clip_block_14 Transformer Block	13M	576 × 1024	txt_block_7 Transformer Block	3.2M	77 × 512
21	changed embedDim, numHeads, ffDim	clip_block_15 Transformer Block	13M	576 × 1024	vis_block_8 Transformer Block	7.1M	49 × 768
22	changed embedDim, numHeads, ffDim	clip_block_16 Transformer Block	13M	576 × 1024	txt_block_8 Transformer Block	3.2M	77 × 512
23	changed embedDim, numHeads, ffDim	clip_block_17 Transformer Block	13M	576 × 1024	vis_block_9 Transformer Block	7.1M	49 × 768
24	changed embedDim, numHeads, ffDim	clip_block_18 Transformer Block	13M	576 × 1024	txt_block_9 Transformer Block	3.2M	77 × 512
25	changed embedDim, numHeads, ffDim	clip_block_19 Transformer Block	13M	576 × 1024	vis_block_10 Transformer Block	7.1M	49 × 768
26	changed embedDim, numHeads, ffDim	clip_block_20 Transformer Block	13M	576 × 1024	txt_block_10 Transformer Block	3.2M	77 × 512
27	changed embedDim, numHeads, ffDim	clip_block_21 Transformer Block	13M	576 × 1024	vis_block_11 Transformer Block	7.1M	49 × 768
28	changed embedDim, numHeads, ffDim	clip_block_22 Transformer Block	13M	576 × 1024	txt_block_11 Transformer Block	3.2M	77 × 512
29	changed embedDim, numHeads, ffDim	clip_block_23 Transformer Block	13M	576 × 1024	vis_block_12 Transformer Block	7.1M	49 × 768
30	changed embedDim, numHeads, ffDim	clip_block_24 Transformer Block	13M	576 × 1024	txt_block_12 Transformer Block	3.2M	77 × 512
31	removed	projector_1 Linear	4.2M	576 × 4096	—
32	removed	projector_gelu Gelu		576 × 4096	—
33	removed	projector_2 Linear	17M	576 × 4096	—
34	removed	vision_tokens Reshape		1 × 576 × 4096	—
35	removed	image+text_tokens Concatenate		1 × 2624 × 4096	—
36	removed	llm_attn_norm_1 Rms Norm	4.1K	1 × 2624 × 4096	—
37	removed	llm_attn_1 Grouped Query Attention	67M	1 × 2624 × 4096	—
38	removed	llm_res1_1 Add		1 × 2624 × 4096	—
39	removed	llm_ffn_norm_1 Rms Norm	4.1K	1 × 2624 × 4096	—
40	removed	llm_ffn_1 Swiglu	135M	1 × 2624 × 4096	—
41	removed	llm_res2_1 Add		1 × 2624 × 4096	—
42	removed	llm_attn_norm_2 Rms Norm	4.1K	1 × 2624 × 4096	—
43	removed	llm_attn_2 Grouped Query Attention	67M	1 × 2624 × 4096	—
44	removed	llm_res1_2 Add		1 × 2624 × 4096	—
45	removed	llm_ffn_norm_2 Rms Norm	4.1K	1 × 2624 × 4096	—
46	removed	llm_ffn_2 Swiglu	135M	1 × 2624 × 4096	—
47	removed	llm_res2_2 Add		1 × 2624 × 4096	—
48	removed	llm_attn_norm_3 Rms Norm	4.1K	1 × 2624 × 4096	—
49	removed	llm_attn_3 Grouped Query Attention	67M	1 × 2624 × 4096	—
50	removed	llm_res1_3 Add		1 × 2624 × 4096	—
51	removed	llm_ffn_norm_3 Rms Norm	4.1K	1 × 2624 × 4096	—
52	removed	llm_ffn_3 Swiglu	135M	1 × 2624 × 4096	—
53	removed	llm_res2_3 Add		1 × 2624 × 4096	—
54	removed	llm_attn_norm_4 Rms Norm	4.1K	1 × 2624 × 4096	—
55	removed	llm_attn_4 Grouped Query Attention	67M	1 × 2624 × 4096	—
56	removed	llm_res1_4 Add		1 × 2624 × 4096	—
57	removed	llm_ffn_norm_4 Rms Norm	4.1K	1 × 2624 × 4096	—
58	removed	llm_ffn_4 Swiglu	135M	1 × 2624 × 4096	—
59	removed	llm_res2_4 Add		1 × 2624 × 4096	—
60	removed	llm_attn_norm_5 Rms Norm	4.1K	1 × 2624 × 4096	—
61	removed	llm_attn_5 Grouped Query Attention	67M	1 × 2624 × 4096	—
62	removed	llm_res1_5 Add		1 × 2624 × 4096	—
63	removed	llm_ffn_norm_5 Rms Norm	4.1K	1 × 2624 × 4096	—
64	removed	llm_ffn_5 Swiglu	135M	1 × 2624 × 4096	—
65	removed	llm_res2_5 Add		1 × 2624 × 4096	—
66	removed	llm_attn_norm_6 Rms Norm	4.1K	1 × 2624 × 4096	—
67	removed	llm_attn_6 Grouped Query Attention	67M	1 × 2624 × 4096	—
68	removed	llm_res1_6 Add		1 × 2624 × 4096	—
69	removed	llm_ffn_norm_6 Rms Norm	4.1K	1 × 2624 × 4096	—
70	removed	llm_ffn_6 Swiglu	135M	1 × 2624 × 4096	—
71	removed	llm_res2_6 Add		1 × 2624 × 4096	—
72	removed	llm_attn_norm_7 Rms Norm	4.1K	1 × 2624 × 4096	—
73	removed	llm_attn_7 Grouped Query Attention	67M	1 × 2624 × 4096	—
74	removed	llm_res1_7 Add		1 × 2624 × 4096	—
75	removed	llm_ffn_norm_7 Rms Norm	4.1K	1 × 2624 × 4096	—
76	removed	llm_ffn_7 Swiglu	135M	1 × 2624 × 4096	—
77	removed	llm_res2_7 Add		1 × 2624 × 4096	—
78	removed	llm_attn_norm_8 Rms Norm	4.1K	1 × 2624 × 4096	—
79	removed	llm_attn_8 Grouped Query Attention	67M	1 × 2624 × 4096	—
80	removed	llm_res1_8 Add		1 × 2624 × 4096	—
81	removed	llm_ffn_norm_8 Rms Norm	4.1K	1 × 2624 × 4096	—
82	removed	llm_ffn_8 Swiglu	135M	1 × 2624 × 4096	—
83	removed	llm_res2_8 Add		1 × 2624 × 4096	—
84	removed	llm_attn_norm_9 Rms Norm	4.1K	1 × 2624 × 4096	—
85	removed	llm_attn_9 Grouped Query Attention	67M	1 × 2624 × 4096	—
86	removed	llm_res1_9 Add		1 × 2624 × 4096	—
87	removed	llm_ffn_norm_9 Rms Norm	4.1K	1 × 2624 × 4096	—
88	removed	llm_ffn_9 Swiglu	135M	1 × 2624 × 4096	—
89	removed	llm_res2_9 Add		1 × 2624 × 4096	—
90	removed	llm_attn_norm_10 Rms Norm	4.1K	1 × 2624 × 4096	—
91	removed	llm_attn_10 Grouped Query Attention	67M	1 × 2624 × 4096	—
92	removed	llm_res1_10 Add		1 × 2624 × 4096	—
93	removed	llm_ffn_norm_10 Rms Norm	4.1K	1 × 2624 × 4096	—
94	removed	llm_ffn_10 Swiglu	135M	1 × 2624 × 4096	—
95	removed	llm_res2_10 Add		1 × 2624 × 4096	—
96	removed	llm_attn_norm_11 Rms Norm	4.1K	1 × 2624 × 4096	—
97	removed	llm_attn_11 Grouped Query Attention	67M	1 × 2624 × 4096	—
98	removed	llm_res1_11 Add		1 × 2624 × 4096	—
99	removed	llm_ffn_norm_11 Rms Norm	4.1K	1 × 2624 × 4096	—
100	removed	llm_ffn_11 Swiglu	135M	1 × 2624 × 4096	—
101	removed	llm_res2_11 Add		1 × 2624 × 4096	—
102	removed	llm_attn_norm_12 Rms Norm	4.1K	1 × 2624 × 4096	—
103	removed	llm_attn_12 Grouped Query Attention	67M	1 × 2624 × 4096	—
104	removed	llm_res1_12 Add		1 × 2624 × 4096	—
105	removed	llm_ffn_norm_12 Rms Norm	4.1K	1 × 2624 × 4096	—
106	removed	llm_ffn_12 Swiglu	135M	1 × 2624 × 4096	—
107	removed	llm_res2_12 Add		1 × 2624 × 4096	—
108	removed	llm_attn_norm_13 Rms Norm	4.1K	1 × 2624 × 4096	—
109	removed	llm_attn_13 Grouped Query Attention	67M	1 × 2624 × 4096	—
110	removed	llm_res1_13 Add		1 × 2624 × 4096	—
111	removed	llm_ffn_norm_13 Rms Norm	4.1K	1 × 2624 × 4096	—
112	removed	llm_ffn_13 Swiglu	135M	1 × 2624 × 4096	—
113	removed	llm_res2_13 Add		1 × 2624 × 4096	—
114	removed	llm_attn_norm_14 Rms Norm	4.1K	1 × 2624 × 4096	—
115	removed	llm_attn_14 Grouped Query Attention	67M	1 × 2624 × 4096	—
116	removed	llm_res1_14 Add		1 × 2624 × 4096	—
117	removed	llm_ffn_norm_14 Rms Norm	4.1K	1 × 2624 × 4096	—
118	removed	llm_ffn_14 Swiglu	135M	1 × 2624 × 4096	—
119	removed	llm_res2_14 Add		1 × 2624 × 4096	—
120	removed	llm_attn_norm_15 Rms Norm	4.1K	1 × 2624 × 4096	—
121	removed	llm_attn_15 Grouped Query Attention	67M	1 × 2624 × 4096	—
122	removed	llm_res1_15 Add		1 × 2624 × 4096	—
123	removed	llm_ffn_norm_15 Rms Norm	4.1K	1 × 2624 × 4096	—
124	removed	llm_ffn_15 Swiglu	135M	1 × 2624 × 4096	—
125	removed	llm_res2_15 Add		1 × 2624 × 4096	—
126	removed	llm_attn_norm_16 Rms Norm	4.1K	1 × 2624 × 4096	—
127	removed	llm_attn_16 Grouped Query Attention	67M	1 × 2624 × 4096	—
128	removed	llm_res1_16 Add		1 × 2624 × 4096	—
129	removed	llm_ffn_norm_16 Rms Norm	4.1K	1 × 2624 × 4096	—
130	removed	llm_ffn_16 Swiglu	135M	1 × 2624 × 4096	—
131	removed	llm_res2_16 Add		1 × 2624 × 4096	—
132	removed	llm_attn_norm_17 Rms Norm	4.1K	1 × 2624 × 4096	—
133	removed	llm_attn_17 Grouped Query Attention	67M	1 × 2624 × 4096	—
134	removed	llm_res1_17 Add		1 × 2624 × 4096	—
135	removed	llm_ffn_norm_17 Rms Norm	4.1K	1 × 2624 × 4096	—
136	removed	llm_ffn_17 Swiglu	135M	1 × 2624 × 4096	—
137	removed	llm_res2_17 Add		1 × 2624 × 4096	—
138	removed	llm_attn_norm_18 Rms Norm	4.1K	1 × 2624 × 4096	—
139	removed	llm_attn_18 Grouped Query Attention	67M	1 × 2624 × 4096	—
140	removed	llm_res1_18 Add		1 × 2624 × 4096	—
141	removed	llm_ffn_norm_18 Rms Norm	4.1K	1 × 2624 × 4096	—
142	removed	llm_ffn_18 Swiglu	135M	1 × 2624 × 4096	—
143	removed	llm_res2_18 Add		1 × 2624 × 4096	—
144	removed	llm_attn_norm_19 Rms Norm	4.1K	1 × 2624 × 4096	—
145	removed	llm_attn_19 Grouped Query Attention	67M	1 × 2624 × 4096	—
146	removed	llm_res1_19 Add		1 × 2624 × 4096	—
147	removed	llm_ffn_norm_19 Rms Norm	4.1K	1 × 2624 × 4096	—
148	removed	llm_ffn_19 Swiglu	135M	1 × 2624 × 4096	—
149	removed	llm_res2_19 Add		1 × 2624 × 4096	—
150	removed	llm_attn_norm_20 Rms Norm	4.1K	1 × 2624 × 4096	—
151	removed	llm_attn_20 Grouped Query Attention	67M	1 × 2624 × 4096	—
152	removed	llm_res1_20 Add		1 × 2624 × 4096	—
153	removed	llm_ffn_norm_20 Rms Norm	4.1K	1 × 2624 × 4096	—
154	removed	llm_ffn_20 Swiglu	135M	1 × 2624 × 4096	—
155	removed	llm_res2_20 Add		1 × 2624 × 4096	—
156	removed	llm_attn_norm_21 Rms Norm	4.1K	1 × 2624 × 4096	—
157	removed	llm_attn_21 Grouped Query Attention	67M	1 × 2624 × 4096	—
158	removed	llm_res1_21 Add		1 × 2624 × 4096	—
159	removed	llm_ffn_norm_21 Rms Norm	4.1K	1 × 2624 × 4096	—
160	removed	llm_ffn_21 Swiglu	135M	1 × 2624 × 4096	—
161	removed	llm_res2_21 Add		1 × 2624 × 4096	—
162	removed	llm_attn_norm_22 Rms Norm	4.1K	1 × 2624 × 4096	—
163	removed	llm_attn_22 Grouped Query Attention	67M	1 × 2624 × 4096	—
164	removed	llm_res1_22 Add		1 × 2624 × 4096	—
165	removed	llm_ffn_norm_22 Rms Norm	4.1K	1 × 2624 × 4096	—
166	removed	llm_ffn_22 Swiglu	135M	1 × 2624 × 4096	—
167	removed	llm_res2_22 Add		1 × 2624 × 4096	—
168	removed	llm_attn_norm_23 Rms Norm	4.1K	1 × 2624 × 4096	—
169	removed	llm_attn_23 Grouped Query Attention	67M	1 × 2624 × 4096	—
170	removed	llm_res1_23 Add		1 × 2624 × 4096	—
171	removed	llm_ffn_norm_23 Rms Norm	4.1K	1 × 2624 × 4096	—
172	removed	llm_ffn_23 Swiglu	135M	1 × 2624 × 4096	—
173	removed	llm_res2_23 Add		1 × 2624 × 4096	—
174	removed	llm_attn_norm_24 Rms Norm	4.1K	1 × 2624 × 4096	—
175	removed	llm_attn_24 Grouped Query Attention	67M	1 × 2624 × 4096	—
176	removed	llm_res1_24 Add		1 × 2624 × 4096	—
177	removed	llm_ffn_norm_24 Rms Norm	4.1K	1 × 2624 × 4096	—
178	removed	llm_ffn_24 Swiglu	135M	1 × 2624 × 4096	—
179	removed	llm_res2_24 Add		1 × 2624 × 4096	—
180	removed	llm_attn_norm_25 Rms Norm	4.1K	1 × 2624 × 4096	—
181	removed	llm_attn_25 Grouped Query Attention	67M	1 × 2624 × 4096	—
182	removed	llm_res1_25 Add		1 × 2624 × 4096	—
183	removed	llm_ffn_norm_25 Rms Norm	4.1K	1 × 2624 × 4096	—
184	removed	llm_ffn_25 Swiglu	135M	1 × 2624 × 4096	—
185	removed	llm_res2_25 Add		1 × 2624 × 4096	—
186	removed	llm_attn_norm_26 Rms Norm	4.1K	1 × 2624 × 4096	—
187	removed	llm_attn_26 Grouped Query Attention	67M	1 × 2624 × 4096	—
188	removed	llm_res1_26 Add		1 × 2624 × 4096	—
189	removed	llm_ffn_norm_26 Rms Norm	4.1K	1 × 2624 × 4096	—
190	removed	llm_ffn_26 Swiglu	135M	1 × 2624 × 4096	—
191	removed	llm_res2_26 Add		1 × 2624 × 4096	—
192	removed	llm_attn_norm_27 Rms Norm	4.1K	1 × 2624 × 4096	—
193	removed	llm_attn_27 Grouped Query Attention	67M	1 × 2624 × 4096	—
194	removed	llm_res1_27 Add		1 × 2624 × 4096	—
195	removed	llm_ffn_norm_27 Rms Norm	4.1K	1 × 2624 × 4096	—
196	removed	llm_ffn_27 Swiglu	135M	1 × 2624 × 4096	—
197	removed	llm_res2_27 Add		1 × 2624 × 4096	—
198	removed	llm_attn_norm_28 Rms Norm	4.1K	1 × 2624 × 4096	—
199	removed	llm_attn_28 Grouped Query Attention	67M	1 × 2624 × 4096	—
200	removed	llm_res1_28 Add		1 × 2624 × 4096	—
201	removed	llm_ffn_norm_28 Rms Norm	4.1K	1 × 2624 × 4096	—
202	removed	llm_ffn_28 Swiglu	135M	1 × 2624 × 4096	—
203	removed	llm_res2_28 Add		1 × 2624 × 4096	—
204	removed	llm_attn_norm_29 Rms Norm	4.1K	1 × 2624 × 4096	—
205	removed	llm_attn_29 Grouped Query Attention	67M	1 × 2624 × 4096	—
206	removed	llm_res1_29 Add		1 × 2624 × 4096	—
207	removed	llm_ffn_norm_29 Rms Norm	4.1K	1 × 2624 × 4096	—
208	removed	llm_ffn_29 Swiglu	135M	1 × 2624 × 4096	—
209	removed	llm_res2_29 Add		1 × 2624 × 4096	—
210	removed	llm_attn_norm_30 Rms Norm	4.1K	1 × 2624 × 4096	—
211	removed	llm_attn_30 Grouped Query Attention	67M	1 × 2624 × 4096	—
212	removed	llm_res1_30 Add		1 × 2624 × 4096	—
213	removed	llm_ffn_norm_30 Rms Norm	4.1K	1 × 2624 × 4096	—
214	removed	llm_ffn_30 Swiglu	135M	1 × 2624 × 4096	—
215	removed	llm_res2_30 Add		1 × 2624 × 4096	—
216	removed	llm_attn_norm_31 Rms Norm	4.1K	1 × 2624 × 4096	—
217	removed	llm_attn_31 Grouped Query Attention	67M	1 × 2624 × 4096	—
218	removed	llm_res1_31 Add		1 × 2624 × 4096	—
219	removed	llm_ffn_norm_31 Rms Norm	4.1K	1 × 2624 × 4096	—
220	removed	llm_ffn_31 Swiglu	135M	1 × 2624 × 4096	—
221	removed	llm_res2_31 Add		1 × 2624 × 4096	—
222	removed	llm_attn_norm_32 Rms Norm	4.1K	1 × 2624 × 4096	—
223	removed	llm_attn_32 Grouped Query Attention	67M	1 × 2624 × 4096	—
224	removed	llm_res1_32 Add		1 × 2624 × 4096	—
225	changed type, normalizedShape	llm_ffn_norm_32 Rms Norm	4.1K	1 × 2624 × 4096	vis_norm Layer Norm	1.5K	49 × 768
226	removed	llm_ffn_32 Swiglu	135M	1 × 2624 × 4096	—
227	removed	llm_res2_32 Add		1 × 2624 × 4096	—
228	changed type, normalizedShape	final_norm Rms Norm	4.1K	1 × 2624 × 4096	txt_norm Layer Norm	1.0K	77 × 512
229	added	—			to_channels_vis Permute		768 × 49
230	added	—			to_channels_txt Permute		512 × 77
231	added	—			vis_pool Global Avg Pool1d		768
232	added	—			txt_pool Global Avg Pool1d		512
233	added	—			img_proj Linear	394K	512
234	changed inFeatures, outFeatures, bias	lm_head Linear	131M	1 × 2624 × 32000	txt_proj Linear	263K	512
235	added	—			similarity Matmul		512
236	same	logits Output		1 × 2624 × 32000	logits Output		512

What this is not

The two are priced at different declared inputs (3 × 336 × 336 against 3 × 224 × 224), so memory, cost and GPU fit are each right about their own model and are not a comparison between them. The layer and parameter deltas are unaffected.
Parameter counts are derived from the graph, not read from a checkpoint. They are exact for a graph that is fully specified and approximate for one that is not.
Cost and GPU fit are estimates from the graph under one set of assumptions, not measurements of a run.

Take it further

Open either graph in the editor, change it, and check it again: LLaVA-1.5 · CLIP ViT-B/32

Compare any two models of your own, including anything on Hugging Face: the comparison tool.

Machine-readable: this page as markdown · the pair index · POST https://www.neurarch.com/api/v1/plan for a graph of your own.