Head-to-head comparison across 3benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
DeepSeek V3
35
Ling 2.6 Flash
36
Pick Ling 2.6 Flash if you want the stronger benchmark profile. DeepSeek V3 only becomes the better choice if instruction following is the priority.
Coding
+12.2 difference
Knowledge
+11.0 difference
Inst. Following
+29.1 difference
DeepSeek V3
Ling 2.6 Flash
$0.27 / $1.1
$null / $null
N/A
209.5 t/s
N/A
1.07s
128K
262K
Pick Ling 2.6 Flash if you want the stronger benchmark profile. DeepSeek V3 only becomes the better choice if instruction following is the priority.
Ling 2.6 Flash finishes one point ahead on BenchLM's provisional leaderboard, 36 to 35. That is enough to call, but not enough to treat as a blowout. This matchup comes down to a few meaningful edges rather than one model dominating the board.
Ling 2.6 Flash gives you the larger context window at 262K, compared with 128K for DeepSeek V3.
Ling 2.6 Flash is ahead on BenchLM's provisional leaderboard, 36 to 35. The biggest single separator in this matchup is GPQA, where the scores are 59.1% and 59%.
DeepSeek V3 has the edge for knowledge tasks in this comparison, averaging 70 versus 59. Inside this category, AA-Omniscience Index is the benchmark that creates the most daylight between them.
DeepSeek V3 has the edge for coding in this comparison, averaging 39.2 versus 27. Inside this category, Terminal-Bench Hard is the benchmark that creates the most daylight between them.
DeepSeek V3 has the edge for instruction following in this comparison, averaging 86.1 versus 57. Inside this category, AA-IFBench is the benchmark that creates the most daylight between them.
Estimates at 50,000 req/day · 1000 tokens/req average.
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