DMC to Anchor thread conversion chart
Find the closest Anchor match for any DMC color — with match quality percentages and ranked alternatives. Also converts Anchor to DMC.
489 colors matched using perceptual color distance.
Full DMC to Anchor conversion chart
489 color matches, ranked by match quality. Click any row for alternatives.
| Code | → | Code | Match | ||
|---|---|---|---|---|---|
| B5200 | → | 2 | 87% Good | ||
| BLANC | → | 2 | 98% Best | ||
| ECRU | → | 885 | 87% Good | ||
| 01 | → | 234 | 83% Fair | ||
| 02 | → | 274 | 74% Approx | ||
| 03 | → | 398 | 88% Good | ||
| 04 | → | 399 | 95% Best | ||
| 05 | → | 388 | 86% Good | ||
| 06 | → | 391 | 85% Good | ||
| 07 | → | 233 | 76% Fair | ||
| 08 | → | 903 | 77% Fair | ||
| 09 | → | 1086 | 73% Approx | ||
| 10 | → | 213 | 87% Good | ||
| 11 | → | 278 | 82% Fair | ||
| 12 | → | 278 | 89% Good | ||
| 13 | → | 203 | 90% Good | ||
| 14 | → | 253 | 66% Approx | ||
| 15 | → | 278 | 72% Approx | ||
| 16 | → | 254 | 74% Approx | ||
| 17 | → | 278 | 80% Fair | ||
| 18 | → | 295 | 71% Approx | ||
| 19 | → | 372 | 74% Approx | ||
| 20 | → | 1010 | 90% Good | ||
| 21 | → | 1013 | 82% Fair | ||
| 22 | → | 1025 | 81% Fair | ||
| 23 | → | 1026 | 68% Approx | ||
| 24 | → | 234 | 62% Approx | ||
| 25 | → | 234 | 67% Approx | ||
| 26 | → | 95 | 65% Approx | ||
| 27 | → | 234 | 73% Approx | ||
| 28 | → | 118 | 79% Fair | ||
| 29 | → | 122 | 78% Fair | ||
| 30 | → | 136 | 70% Approx | ||
| 31 | → | 176 | 91% Good | ||
| 32 | → | 176 | 77% Fair | ||
| 33 | → | 110 | 86% Good | ||
| 34 | → | 99 | 81% Fair | ||
| 35 | → | 100 | 85% Good | ||
| 150 | → | 43 | 85% Good | ||
| 151 | → | 49 | 88% Good | ||
| 152 | → | 969 | 77% Fair | ||
| 153 | → | 90 | 81% Fair | ||
| 154 | → | 873 | 79% Fair | ||
| 155 | → | 1030 | 90% Good | ||
| 156 | → | 136 | 82% Fair | ||
| 157 | → | 140 | 86% Good | ||
| 158 | → | 177 | 83% Fair | ||
| 159 | → | 175 | 85% Good | ||
| 160 | → | 121 | 77% Fair | ||
| 161 | → | 131 | 95% Best | ||
| 162 | → | 160 | 79% Fair | ||
| 163 | → | 205 | 80% Fair | ||
| 164 | → | 241 | 73% Approx | ||
| 165 | → | 278 | 90% Good | ||
| 166 | → | 279 | 69% Approx | ||
| 167 | → | 373 | 93% Best | ||
| 168 | → | 274 | 92% Good | ||
| 169 | → | 849 | 76% Fair | ||
| 208 | → | 110 | 87% Good | ||
| 209 | → | 109 | 87% Good | ||
| 210 | → | 108 | 89% Good | ||
| 211 | → | 342 | 95% Best | ||
| 221 | → | 45 | 86% Good | ||
| 223 | → | 1023 | 84% Fair | ||
| 224 | → | 894 | 91% Good | ||
| 225 | → | 968 | 83% Fair | ||
| 300 | → | 352 | 73% Approx | ||
| 301 | → | 340 | 80% Fair | ||
| 304 | → | 20 | 94% Best | ||
| 307 | → | 289 | 80% Fair | ||
| 309 | → | 19 | 97% Best | ||
| 310 | → | 403 | 90% Good | ||
| 311 | → | 147 | 91% Good | ||
| 312 | → | 142 | 85% Good | ||
| 315 | → | 972 | 82% Fair | ||
| 316 | → | 1017 | 80% Fair | ||
| 317 | → | 978 | 75% Fair | ||
| 318 | → | 920 | 88% Good | ||
| 319 | → | 212 | 90% Good | ||
| 320 | → | 215 | 89% Good | ||
| 321 | → | 20 | 74% Approx | ||
| 322 | → | 410 | 74% Approx | ||
| 326 | → | 19 | 90% Good | ||
| 327 | → | 100 | 81% Fair | ||
| 333 | → | 119 | 74% Approx | ||
| 334 | → | 161 | 63% Approx | ||
| 335 | → | 35 | 91% Good | ||
| 336 | → | 139 | 92% Good | ||
| 340 | → | 118 | 78% Fair | ||
| 341 | → | 175 | 87% Good | ||
| 347 | → | 19 | 80% Fair | ||
| 349 | → | 29 | 82% Fair | ||
| 350 | → | 1098 | 85% Good | ||
| 351 | → | 11 | 89% Good | ||
| 352 | → | 10 | 81% Fair | ||
| 353 | → | 8 | 82% Fair | ||
| 355 | → | 1025 | 83% Fair | ||
| 356 | → | 1024 | 69% Approx | ||
| 367 | → | 216 | 85% Good | ||
| 368 | → | 204 | 79% Fair | ||
| 369 | → | 260 | 70% Approx | ||
| 370 | → | 280 | 86% Good | ||
| 371 | → | 280 | 75% Fair | ||
| 372 | → | 945 | 89% Good | ||
| 400 | → | 1004 | 72% Approx | ||
| 402 | → | 323 | 84% Fair | ||
| 407 | → | 914 | 81% Fair | ||
| 413 | → | 235 | 79% Fair | ||
| 414 | → | 939 | 95% Best | ||
| 415 | → | 1033 | 74% Approx | ||
| 420 | → | 373 | 88% Good | ||
| 422 | → | 874 | 86% Good | ||
| 433 | → | 358 | 82% Fair | ||
| 434 | → | 370 | 85% Good | ||
| 435 | → | 1048 | 86% Good | ||
| 436 | → | 363 | 79% Fair | ||
| 437 | → | 347 | 79% Fair | ||
| 444 | → | 290 | 87% Good | ||
| 445 | → | 288 | 88% Good | ||
| 451 | → | 233 | 76% Fair | ||
| 452 | → | 232 | 75% Fair | ||
| 453 | → | 388 | 91% Good | ||
| 469 | → | 267 | 90% Good | ||
| 470 | → | 266 | 85% Good | ||
| 471 | → | 265 | 88% Good | ||
| 472 | → | 278 | 70% Approx | ||
| 498 | → | 22 | 90% Good | ||
| 500 | → | 189 | 87% Good | ||
| 501 | → | 217 | 80% Fair | ||
| 502 | → | 876 | 82% Fair | ||
| 503 | → | 214 | 65% Approx | ||
| 505 | → | 216 | 83% Fair | ||
| 517 | → | 410 | 72% Approx | ||
| 518 | → | 161 | 79% Fair | ||
| 519 | → | 1038 | 79% Fair | ||
| 520 | → | 861 | 85% Good | ||
| 522 | → | 859 | 91% Good | ||
| 523 | → | 261 | 82% Fair | ||
| 524 | → | 261 | 62% Approx | ||
| 535 | → | 235 | 84% Fair | ||
| 543 | → | 366 | 95% Best | ||
| 550 | → | 112 | 87% Good | ||
| 552 | → | 110 | 75% Fair | ||
| 553 | → | 92 | 89% Good | ||
| 554 | → | 96 | 82% Fair | ||
| 561 | → | 877 | 88% Good | ||
| 562 | → | 215 | 77% Fair | ||
| 563 | → | 1072 | 79% Fair | ||
| 564 | → | 203 | 82% Fair | ||
| 580 | → | 267 | 81% Fair | ||
| 581 | → | 266 | 77% Fair | ||
| 597 | → | 1064 | 72% Approx | ||
| 598 | → | 167 | 72% Approx | ||
| 600 | → | 19 | 76% Fair | ||
| 601 | → | 42 | 76% Fair | ||
| 602 | → | 35 | 76% Fair | ||
| 603 | → | 54 | 82% Fair | ||
| 604 | → | 52 | 82% Fair | ||
| 605 | → | 1094 | 93% Best | ||
| 606 | → | 1098 | 74% Approx | ||
| 608 | → | 925 | 77% Fair | ||
| 610 | → | 898 | 81% Fair | ||
| 611 | → | 832 | 82% Fair | ||
| 612 | → | 1084 | 74% Approx | ||
| 613 | → | 874 | 82% Fair | ||
| 632 | → | 896 | 74% Approx | ||
| 640 | → | 392 | 73% Approx | ||
| 642 | → | 853 | 75% Fair | ||
| 644 | → | 887 | 79% Fair | ||
| 645 | → | 860 | 92% Good | ||
| 646 | → | 233 | 70% Approx | ||
| 647 | → | 900 | 83% Fair | ||
| 648 | → | 848 | 72% Approx | ||
| 666 | → | 1098 | 85% Good | ||
| 676 | → | 311 | 86% Good | ||
| 677 | → | 300 | 73% Approx | ||
| 680 | → | 1045 | 93% Best | ||
| 699 | → | 210 | 70% Approx | ||
| 700 | → | 227 | 63% Approx | ||
| 701 | → | 227 | 72% Approx | ||
| 702 | → | 239 | 71% Approx | ||
| 703 | → | 238 | 74% Approx | ||
| 704 | → | 238 | 71% Approx | ||
| 712 | → | 885 | 87% Good | ||
| 718 | → | 88 | 89% Good | ||
| 720 | → | 335 | 91% Good | ||
| 721 | → | 316 | 86% Good | ||
| 722 | → | 329 | 86% Good | ||
| 725 | → | 297 | 81% Fair | ||
| 726 | → | 295 | 92% Good | ||
| 727 | → | 293 | 85% Good | ||
| 728 | → | 298 | 82% Fair | ||
| 729 | → | 890 | 90% Good | ||
| 730 | → | 281 | 84% Fair | ||
| 732 | → | 855 | 69% Approx | ||
| 733 | → | 279 | 65% Approx | ||
| 734 | → | 279 | 94% Best | ||
| 738 | → | 942 | 86% Good | ||
| 739 | → | 1080 | 88% Good | ||
| 740 | → | 330 | 91% Good | ||
| 741 | → | 314 | 78% Fair | ||
| 742 | → | 298 | 86% Good | ||
| 743 | → | 290 | 85% Good | ||
| 744 | → | 293 | 91% Good | ||
| 745 | → | 292 | 84% Fair | ||
| 746 | → | 386 | 94% Best | ||
| 747 | → | 928 | 87% Good | ||
| 754 | → | 8 | 88% Good | ||
| 758 | → | 9575 | 86% Good | ||
| 760 | → | 26 | 86% Good | ||
| 761 | → | 24 | 92% Good | ||
| 762 | → | 234 | 87% Good | ||
| 772 | → | 264 | 61% Approx | ||
| 775 | → | 159 | 82% Fair | ||
| 777 | → | 45 | 79% Fair | ||
| 778 | → | 1016 | 96% Best | ||
| 779 | → | 1086 | 78% Fair | ||
| 780 | → | 1049 | 89% Good | ||
| 782 | → | 308 | 83% Fair | ||
| 783 | → | 307 | 89% Good | ||
| 791 | → | 177 | 86% Good | ||
| 792 | → | 132 | 72% Approx | ||
| 793 | → | 131 | 81% Fair | ||
| 794 | → | 136 | 76% Fair | ||
| 796 | → | 133 | 70% Approx | ||
| 797 | → | 132 | 72% Approx | ||
| 798 | → | 410 | 80% Fair | ||
| 799 | → | 161 | 63% Approx | ||
| 800 | → | 140 | 85% Good | ||
| 801 | → | 936 | 84% Fair | ||
| 803 | → | 147 | 87% Good | ||
| 807 | → | 1039 | 74% Approx | ||
| 809 | → | 1039 | 84% Fair | ||
| 813 | → | 1038 | 86% Good | ||
| 814 | → | 1019 | 76% Fair | ||
| 815 | → | 22 | 82% Fair | ||
| 816 | → | 20 | 84% Fair | ||
| 817 | → | 1015 | 83% Fair | ||
| 818 | → | 23 | 89% Good | ||
| 819 | → | 1026 | 83% Fair | ||
| 820 | → | 133 | 84% Fair | ||
| 822 | → | 276 | 89% Good | ||
| 823 | → | 941 | 81% Fair | ||
| 824 | → | 142 | 80% Fair | ||
| 825 | → | 142 | 82% Fair | ||
| 826 | → | 410 | 66% Approx | ||
| 827 | → | 1038 | 92% Good | ||
| 828 | → | 928 | 77% Fair | ||
| 829 | → | 889 | 85% Good | ||
| 830 | → | 1088 | 89% Good | ||
| 831 | → | 907 | 86% Good | ||
| 832 | → | 1045 | 70% Approx | ||
| 833 | → | 874 | 70% Approx | ||
| 834 | → | 279 | 66% Approx | ||
| 838 | → | 936 | 82% Fair | ||
| 839 | → | 1086 | 100% Best | ||
| 840 | → | 1007 | 74% Approx | ||
| 841 | → | 378 | 74% Approx | ||
| 842 | → | 347 | 73% Approx | ||
| 844 | → | 8581 | 87% Good | ||
| 869 | → | 370 | 84% Fair | ||
| 890 | → | 230 | 87% Good | ||
| 891 | → | 28 | 74% Approx | ||
| 892 | → | 28 | 75% Fair | ||
| 893 | → | 27 | 87% Good | ||
| 894 | → | 33 | 94% Best | ||
| 895 | → | 212 | 85% Good | ||
| 898 | → | 936 | 91% Good | ||
| 899 | → | 40 | 88% Good | ||
| 900 | → | 335 | 79% Fair | ||
| 902 | → | 1019 | 84% Fair | ||
| 904 | → | 228 | 93% Best | ||
| 905 | → | 227 | 90% Good | ||
| 906 | → | 239 | 83% Fair | ||
| 907 | → | 265 | 73% Approx | ||
| 909 | → | 210 | 65% Approx | ||
| 910 | → | 227 | 57% Approx | ||
| 911 | → | 209 | 63% Approx | ||
| 912 | → | 208 | 62% Approx | ||
| 913 | → | 1072 | 80% Fair | ||
| 915 | → | 69 | 89% Good | ||
| 917 | → | 78 | 77% Fair | ||
| 918 | → | 1015 | 67% Approx | ||
| 919 | → | 1015 | 87% Good | ||
| 920 | → | 340 | 80% Fair | ||
| 921 | → | 339 | 84% Fair | ||
| 922 | → | 324 | 86% Good | ||
| 924 | → | 170 | 80% Fair | ||
| 926 | → | 876 | 70% Approx | ||
| 927 | → | 848 | 71% Approx | ||
| 928 | → | 274 | 81% Fair | ||
| 930 | → | 851 | 83% Fair | ||
| 931 | → | 977 | 91% Good | ||
| 932 | → | 1039 | 77% Fair | ||
| 934 | → | 263 | 82% Fair | ||
| 935 | → | 861 | 93% Best | ||
| 936 | → | 845 | 74% Approx | ||
| 937 | → | 268 | 83% Fair | ||
| 938 | → | 936 | 73% Approx | ||
| 939 | → | 123 | 63% Approx | ||
| 943 | → | 187 | 85% Good | ||
| 945 | → | 1201 | 90% Good | ||
| 946 | → | 925 | 80% Fair | ||
| 947 | → | 925 | 75% Fair | ||
| 948 | → | 892 | 76% Fair | ||
| 950 | → | 1201 | 89% Good | ||
| 951 | → | 1080 | 88% Good | ||
| 954 | → | 203 | 72% Approx | ||
| 955 | → | 203 | 65% Approx | ||
| 956 | → | 27 | 80% Fair | ||
| 957 | → | 52 | 97% Best | ||
| 958 | → | 187 | 74% Approx | ||
| 959 | → | 1074 | 89% Good | ||
| 961 | → | 54 | 83% Fair | ||
| 962 | → | 54 | 81% Fair | ||
| 963 | → | 1020 | 86% Good | ||
| 964 | → | 185 | 82% Fair | ||
| 966 | → | 203 | 92% Good | ||
| 967 | → | 6 | 91% Good | ||
| 970 | → | 330 | 81% Fair | ||
| 972 | → | 298 | 89% Good | ||
| 973 | → | 295 | 82% Fair | ||
| 975 | → | 1004 | 84% Fair | ||
| 976 | → | 1048 | 73% Approx | ||
| 977 | → | 314 | 84% Fair | ||
| 986 | → | 211 | 82% Fair | ||
| 987 | → | 244 | 75% Fair | ||
| 988 | → | 226 | 89% Good | ||
| 989 | → | 242 | 88% Good | ||
| 991 | → | 188 | 77% Fair | ||
| 992 | → | 187 | 86% Good | ||
| 993 | → | 1072 | 81% Fair | ||
| 995 | → | 410 | 56% Approx | ||
| 996 | → | 1039 | 57% Approx | ||
| 3011 | → | 844 | 88% Good | ||
| 3012 | → | 280 | 89% Good | ||
| 3013 | → | 945 | 81% Fair | ||
| 3021 | → | 904 | 79% Fair | ||
| 3022 | → | 854 | 71% Approx | ||
| 3023 | → | 853 | 86% Good | ||
| 3024 | → | 391 | 70% Approx | ||
| 3031 | → | 936 | 78% Fair | ||
| 3032 | → | 853 | 83% Fair | ||
| 3033 | → | 366 | 83% Fair | ||
| 3041 | → | 871 | 70% Approx | ||
| 3042 | → | 870 | 74% Approx | ||
| 3045 | → | 1045 | 88% Good | ||
| 3046 | → | 372 | 73% Approx | ||
| 3047 | → | 956 | 69% Approx | ||
| 3051 | → | 262 | 90% Good | ||
| 3052 | → | 859 | 77% Fair | ||
| 3053 | → | 261 | 86% Good | ||
| 3064 | → | 883 | 83% Fair | ||
| 3072 | → | 213 | 81% Fair | ||
| 3078 | → | 292 | 88% Good | ||
| 3325 | → | 1038 | 83% Fair | ||
| 3326 | → | 36 | 91% Good | ||
| 3328 | → | 1024 | 78% Fair | ||
| 3340 | → | 329 | 71% Approx | ||
| 3341 | → | 328 | 95% Best | ||
| 3345 | → | 245 | 91% Good | ||
| 3346 | → | 267 | 84% Fair | ||
| 3347 | → | 226 | 80% Fair | ||
| 3348 | → | 264 | 74% Approx | ||
| 3350 | → | 19 | 77% Fair | ||
| 3354 | → | 75 | 86% Good | ||
| 3362 | → | 262 | 87% Good | ||
| 3363 | → | 243 | 81% Fair | ||
| 3364 | → | 261 | 78% Fair | ||
| 3371 | → | 401 | 85% Good | ||
| 3607 | → | 87 | 83% Fair | ||
| 3608 | → | 86 | 68% Approx | ||
| 3609 | → | 86 | 74% Approx | ||
| 3685 | → | 65 | 80% Fair | ||
| 3687 | → | 76 | 85% Good | ||
| 3688 | → | 54 | 75% Fair | ||
| 3689 | → | 49 | 96% Best | ||
| 3705 | → | 28 | 76% Fair | ||
| 3706 | → | 27 | 79% Fair | ||
| 3708 | → | 33 | 83% Fair | ||
| 3712 | → | 28 | 77% Fair | ||
| 3713 | → | 23 | 96% Best | ||
| 3716 | → | 50 | 86% Good | ||
| 3721 | → | 39 | 94% Best | ||
| 3722 | → | 1024 | 79% Fair | ||
| 3726 | → | 1018 | 91% Good | ||
| 3727 | → | 1016 | 76% Fair | ||
| 3731 | → | 42 | 91% Good | ||
| 3733 | → | 40 | 85% Good | ||
| 3740 | → | 871 | 85% Good | ||
| 3743 | → | 869 | 88% Good | ||
| 3746 | → | 176 | 67% Approx | ||
| 3747 | → | 117 | 88% Good | ||
| 3750 | → | 979 | 86% Good | ||
| 3752 | → | 1096 | 94% Best | ||
| 3753 | → | 1032 | 93% Best | ||
| 3755 | → | 1039 | 75% Fair | ||
| 3756 | → | 1037 | 91% Good | ||
| 3760 | → | 161 | 57% Approx | ||
| 3761 | → | 167 | 83% Fair | ||
| 3765 | → | 162 | 85% Good | ||
| 3766 | → | 1064 | 85% Good | ||
| 3768 | → | 169 | 75% Fair | ||
| 3770 | → | 1009 | 93% Best | ||
| 3771 | → | 882 | 85% Good | ||
| 3772 | → | 884 | 74% Approx | ||
| 3774 | → | 778 | 87% Good | ||
| 3776 | → | 1013 | 77% Fair | ||
| 3777 | → | 1025 | 86% Good | ||
| 3778 | → | 1013 | 76% Fair | ||
| 3779 | → | 882 | 86% Good | ||
| 3781 | → | 904 | 91% Good | ||
| 3782 | → | 831 | 85% Good | ||
| 3787 | → | 393 | 91% Good | ||
| 3790 | → | 903 | 95% Best | ||
| 3799 | → | 400 | 81% Fair | ||
| 3801 | → | 1098 | 80% Fair | ||
| 3802 | → | 1019 | 86% Good | ||
| 3803 | → | 78 | 87% Good | ||
| 3804 | → | 63 | 77% Fair | ||
| 3805 | → | 62 | 72% Approx | ||
| 3806 | → | 57 | 76% Fair | ||
| 3807 | → | 137 | 86% Good | ||
| 3808 | → | 170 | 79% Fair | ||
| 3809 | → | 1068 | 83% Fair | ||
| 3810 | → | 1066 | 70% Approx | ||
| 3811 | → | 1062 | 78% Fair | ||
| 3812 | → | 1076 | 89% Good | ||
| 3813 | → | 875 | 88% Good | ||
| 3814 | → | 188 | 72% Approx | ||
| 3815 | → | 188 | 80% Fair | ||
| 3816 | → | 209 | 76% Fair | ||
| 3817 | → | 214 | 78% Fair | ||
| 3818 | → | 211 | 80% Fair | ||
| 3819 | → | 278 | 61% Approx | ||
| 3820 | → | 890 | 69% Approx | ||
| 3821 | → | 297 | 77% Fair | ||
| 3822 | → | 305 | 82% Fair | ||
| 3823 | → | 300 | 90% Good | ||
| 3824 | → | 8 | 87% Good | ||
| 3825 | → | 313 | 87% Good | ||
| 3826 | → | 1001 | 85% Good | ||
| 3827 | → | 1047 | 76% Fair | ||
| 3828 | → | 1045 | 91% Good | ||
| 3829 | → | 1045 | 83% Fair | ||
| 3830 | → | 1025 | 71% Approx | ||
| 3831 | → | 19 | 94% Best | ||
| 3832 | → | 42 | 83% Fair | ||
| 3833 | → | 41 | 85% Good | ||
| 3834 | → | 100 | 86% Good | ||
| 3835 | → | 99 | 79% Fair | ||
| 3836 | → | 97 | 87% Good | ||
| 3837 | → | 111 | 78% Fair | ||
| 3838 | → | 146 | 69% Approx | ||
| 3839 | → | 977 | 60% Approx | ||
| 3840 | → | 130 | 81% Fair | ||
| 3841 | → | 1096 | 83% Fair | ||
| 3842 | → | 142 | 74% Approx | ||
| 3843 | → | 161 | 59% Approx | ||
| 3844 | → | 161 | 63% Approx | ||
| 3845 | → | 1064 | 64% Approx | ||
| 3846 | → | 1090 | 78% Fair | ||
| 3847 | → | 189 | 64% Approx | ||
| 3848 | → | 188 | 66% Approx | ||
| 3849 | → | 1076 | 71% Approx | ||
| 3850 | → | 187 | 77% Fair | ||
| 3851 | → | 1074 | 66% Approx | ||
| 3852 | → | 890 | 88% Good | ||
| 3853 | → | 324 | 84% Fair | ||
| 3854 | → | 313 | 83% Fair | ||
| 3855 | → | 891 | 91% Good | ||
| 3856 | → | 1047 | 84% Fair | ||
| 3857 | → | 972 | 73% Approx | ||
| 3858 | → | 896 | 78% Fair | ||
| 3859 | → | 914 | 82% Fair | ||
| 3860 | → | 1007 | 76% Fair | ||
| 3861 | → | 379 | 71% Approx | ||
| 3862 | → | 369 | 76% Fair | ||
| 3863 | → | 369 | 76% Fair | ||
| 3864 | → | 368 | 84% Fair | ||
| 3865 | → | 2 | 82% Fair | ||
| 3866 | → | 387 | 91% Good | ||
| 504 | → | 206 | 83% Fair | ||
| 731 | → | 907 | 59% Approx | ||
| 776 | → | 24 | 97% Best | ||
| 781 | → | 901 | 80% Fair | ||
| 806 | → | 1066 | 76% Fair | ||
| 971 | → | 330 | 91% Good | ||
| 3773 | → | 868 | 92% Good |
Convert between DMC and Anchor thread codes. Each match includes a quality percentage based on perceptual color distance — so you can see how close the substitution actually is, not just which number to use.
Paste multiple codes for batch conversion. Browse alternatives when the best match isn't close enough.
How thread conversion works
DMCand
Anchoruse different numbering systems and slightly different dye formulas — a DMC 310 (Black) converts to Anchor 403, but not every conversion is a perfect match.
Some colors have near-exact equivalents. Others are approximate — close enough for most projects, but you might notice a slight shift in tone if you compare threads side by side. The converter shows you how close each match is so you can decide whether it works for your pattern.
Anchor to DMC conversion
The converter runs in both directions. Paste Anchor codes and it returns the closest DMC equivalents with the same match percentages and ranked alternatives.
Going Anchor → DMC is the easier direction, and it is worth knowing why. DMC produces 489 stranded cotton colors; Anchor produces 446. Every Anchor shade has somewhere to land in the larger DMC range, so reverse conversions tend to score higher. Most European and UK patterns are written in Anchor codes while most online pattern libraries and thread charts default to DMC, which is why this is the direction stitchers outside North America run most often.
Why conversions aren't always exact
Thread manufacturers choose pigments independently. DMC 3371 (Black Brown) and its Anchor equivalent 382 look similar under most lighting, but hold them next to each other in bright daylight and you'll see a difference. For most cross stitch projects, the closest match is close enough. For projects where exact color matters — like matching an existing piece — consider buying both and comparing in person.
There is also a structural reason no conversion chart can be perfect: the two ranges are different sizes. With 489 DMC colors mapping onto 446 Anchor colors, the mapping cannot be one-to-one. Somewhere in the chart, two neighboring DMC shades have to share a single Anchor number. That is not an error in the conversion — it is arithmetic, and it is why a printed chart that lists one confident number per color is quietly lying to you.
Where those collisions land matters. They cluster in the ranges with the finest gradations: skin tones, grays, and the long blue and green families where DMC ships five or six steps between shades and Anchor ships four. Blacks, whites, and strong primaries convert almost perfectly, because there is only one place for them to go.
When no good match exists
If the best match comes back under about 75%, you have four options, roughly in order of how often they are the right call:
- Check the ranked alternatives first. The top result is the closest by perceptual distance, but the second or third option is sometimes better for your pattern — a slightly darker match can read more accurately than a slightly lighter one when the neighboring colors in the design are already light.
- Convert the neighbors too. A color that converts badly in isolation often converts fine as part of a gradient, because what the eye reads is the spacing between shades, not their absolute values. Remap the whole run and judge the result together.
- Blend two strands. One strand each of two adjacent Anchor colors sits between them and can close a gap no single skein covers. This works well for skin tones and sky gradients, less well for flat blocks of a single color where the blend reads as texture.
- Keep the original brand for that one color. Nothing requires a single-brand palette. If one shade in a forty-color pattern refuses to convert, buy that one skein in the original brand and convert the rest.
Substituting mid-project
Converting mid-project is riskier than converting before you start, and the reason is dye lots rather than brands. Every skein carries a dye lot number, and two skeins of the same color from different lots can differ slightly. Introduce a brand change on top of that and you are stacking two sources of variation in the same piece.
If you have to switch mid-project:
- Change the color everywhere it appears, not just where you ran out. A single patch of substituted thread in a background is far more visible than a background stitched entirely in the substitute.
- Start the substitute at a natural boundary — a motif edge, a border, a color block — rather than in the middle of an open field.
- Buy enough to finish. Estimate the remaining stitches for that color with the thread usage calculator and add a skein. Coming back for a third lot of the same substitute is how a two-tone background happens.
- Check the match in daylight before committing. Stitch a few crosses on scrap fabric next to a length of the original. Indoor lighting hides exactly the undertone shifts that bright daylight exposes.
Converting entire palettes
If you have a pattern designed for DMC and want to stitch it with Anchor thread (or vice versa), Stitchmate's palette remapping tool converts every color in your pattern with one click. The editor shows you the before and after so you can spot any conversions that need manual adjustment.
Have a pattern file? Open your PCStitch .pat, Pattern Maker .xsd, or OXS file and remap the entire palette in one click — no manual code lookup needed.
See also: DMC vs Anchor thread — which should you use?
Understanding match quality
Conversions are approximate — DMC and Anchor use different dyes, so even the "best" match may differ in undertone, saturation, or sheen. The match percentage tells you how close they actually are:
- 93–100% — Virtually identical. Hard to tell apart even side-by-side.
- 85–92% — Very close. Minor differences visible only in direct bright light.
- 75–84% — Good match. Noticeable when compared directly, but works well in most projects.
- 60–74% — Approximate. Worth checking alternatives for a closer option.
- Below 60% — Significant difference. Check the alternatives — there may be a better option.
For color-critical work (skin tones, gradient blends), compare real skeins rather than relying on any conversion chart.
FAQ
Is there a perfect DMC to Anchor conversion chart?
How is the match percentage calculated?
Can I convert an entire pattern's thread list at once?
Why does my converted color look different in person?
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