- Rank
- #130
- Total Output Tokens
- 253,807
- Response Time (avg)
- 73.02s
- Total Cost
- $0.881
Seed-2.0-Code (low) vs DeepSeek V4 Pro 0423 (high)
The average score is effectively tied at 8.1 vs 8.1. DeepSeek V4 Pro 0423 (high) has the lower benchmark cost at $0.149 vs $0.881. Seed-2.0-Code (low) is faster at 73.02s vs 91.29s, with pass rates of 78.3% vs 65.2%.
Compared models
- Rank
- #131
- Total Output Tokens
- 211,343
- Response Time (avg)
- 91.29s
- Total Cost
- $0.149
Recommended model
DeepSeek V4 Pro 0423 (high)
It has the best score here (8.1), while costing about 5.9x less than Seed-2.0-Code (low).
Detailed comparison
| Metric | Seed-2.0-Code Seed-2.0-Code low | DeepSeek V4 Pro 0423 DeepSeek V4 Pro 0423 high |
|---|---|---|
| Score | 8.1 | 8.1 |
| Rank | #130 | #131 |
| Reliability | 8.9 | 10.0 |
| Consistency | 7.9 | 7.8 |
| Attempts | 69/69 | 69/69 |
| Tests Correct | ||
| Attempt pass rate | 78.3% | 65.2% |
| Flaky tests | 6 | 6 |
| Total Runs | 69 | 69 |
| Cost per result | 6.288 | 3.717 |
| Total Cost | $0.881 | $0.149 |
| Input Price | $0.500 / 1M | $0.209 / 1M |
| Output Price | $3.000 / 1M | $0.418 / 1M |
| Cache Read Price | N/A | $0.018 / 1M |
| Cache Write Price | N/A | N/A |
| Total Input Tokens | 237,604 | 287,061 |
| Output Tokens | 9,617 | 32,056 |
| Reasoning Tokens | 244,190 | 196,607 |
| Response Time (avg) | 73.02s | 91.29s |
| Response Time (max) | 485.92s | 416.76s |
| Response Time (total) | 1679.49s | 2099.56s |
| Parameters | ~200B total (~20B active) | 1.6T total (49B active) |
| Availability | Closed | Open source |
Cache prices apply to input tokens. Reads reuse cached prompts; writes store them and can cost extra. Output tokens use the output price.
Model generation showcase
Hamster playing table tennis
Prompt: Create a detailed SVG illustration of a hamster playing table tennis.
#130 Seed-2.0-Code
low
Provider returned error
- Cost
- $0.000
- Time
- 0.3s
- Tokens
- 0 tok
#131 DeepSeek V4 Pro 0423
high- Cost
- $0.023
- Time
- 257.6s
- Tokens
- 14,870 tok
Category Breakdown
| Agentic | Score | Consistency | Attempt pass rate | Flaky tests | Tests Correct | Response Time (avg) | Input Tokens | Output Tokens | Reasoning Tokens |
|---|---|---|---|---|---|---|---|---|---|
| Seed-2.0-Code | 10.0 | 10.0 | 100.0% | 0 | 90.18s | 151,947 | 1,475 | 11,023 | |
| DeepSeek V4 Pro 0423 | 10.0 | 10.0 | 100.0% | 0 | 64.54s | 196,304 | 9,128 | 10,091 |
| Anti-AI Tricks | Score | Consistency | Attempt pass rate | Flaky tests | Tests Correct | Response Time (avg) | Input Tokens | Output Tokens | Reasoning Tokens |
|---|---|---|---|---|---|---|---|---|---|
| Seed-2.0-Code | 8.7 | 7.9 | 91.7% | 1 | 39.56s | 930 | 2,650 | 15,987 | |
| DeepSeek V4 Pro 0423 | 5.7 | 5.9 | 58.3% | 2 | 25.70s | 536 | 149 | 3,214 |
| Coding | Score | Consistency | Attempt pass rate | Flaky tests | Tests Correct | Response Time (avg) | Input Tokens | Output Tokens | Reasoning Tokens |
|---|---|---|---|---|---|---|---|---|---|
| Seed-2.0-Code | 7.0 | 7.1 | 55.6% | 1 | 109.70s | 7,948 | 455 | 55,759 | |
| DeepSeek V4 Pro 0423 | 6.3 | 8.7 | 33.3% | 0 | 243.00s | 5,090 | 383 | 84,580 |
| Combined | Score | Consistency | Attempt pass rate | Flaky tests | Tests Correct | Response Time (avg) | Input Tokens | Output Tokens | Reasoning Tokens |
|---|---|---|---|---|---|---|---|---|---|
| Seed-2.0-Code | 7.3 | 5.8 | 83.3% | 1 | 99.12s | 55,969 | 3,774 | 21,408 | |
| DeepSeek V4 Pro 0423 | 10.0 | 10.0 | 100.0% | 0 | 78.99s | 66,082 | 4,582 | 25,404 |
| Data parsing and extraction | Score | Consistency | Attempt pass rate | Flaky tests | Tests Correct | Response Time (avg) | Input Tokens | Output Tokens | Reasoning Tokens |
|---|---|---|---|---|---|---|---|---|---|
| Seed-2.0-Code | 10.0 | 10.0 | 100.0% | 0 | 24.88s | 8,046 | 246 | 1,639 | |
| DeepSeek V4 Pro 0423 | 10.0 | 10.0 | 100.0% | 0 | 25.03s | 7,690 | 274 | 2,166 |
| Domain specific | Score | Consistency | Attempt pass rate | Flaky tests | Tests Correct | Response Time (avg) | Input Tokens | Output Tokens | Reasoning Tokens |
|---|---|---|---|---|---|---|---|---|---|
| Seed-2.0-Code | 4.1 | 4.4 | 44.5% | 2 | 238.45s | 975 | 16 | 132,626 | |
| DeepSeek V4 Pro 0423 | 3.6 | 7.2 | 22.2% | 1 | 249.47s | 578 | 16,870 | 58,188 |
| General Intelligence | Score | Consistency | Attempt pass rate | Flaky tests | Tests Correct | Response Time (avg) | Input Tokens | Output Tokens | Reasoning Tokens |
|---|---|---|---|---|---|---|---|---|---|
| Seed-2.0-Code | 6.5 | 3.4 | 66.7% | 1 | 11.14s | 579 | 179 | 1,117 | |
| DeepSeek V4 Pro 0423 | 10.0 | 10.0 | 100.0% | 0 | 8.83s | 471 | 115 | 1,013 |
| Instructions following | Score | Consistency | Attempt pass rate | Flaky tests | Tests Correct | Response Time (avg) | Input Tokens | Output Tokens | Reasoning Tokens |
|---|---|---|---|---|---|---|---|---|---|
| Seed-2.0-Code | 9.8 | 10.0 | 100.0% | 0 | 12.20s | 828 | 72 | 1,034 | |
| DeepSeek V4 Pro 0423 | 7.8 | 6.6 | 83.3% | 1 | 8.73s | 627 | 66 | 2,726 |
| Puzzle Solving | Score | Consistency | Attempt pass rate | Flaky tests | Tests Correct | Response Time (avg) | Input Tokens | Output Tokens | Reasoning Tokens |
|---|---|---|---|---|---|---|---|---|---|
| Seed-2.0-Code | 9.9 | 10.0 | 100.0% | 0 | 12.50s | 885 | 445 | 2,470 | |
| DeepSeek V4 Pro 0423 | 6.9 | 4.9 | 77.8% | 2 | 56.85s | 591 | 178 | 2,563 |
| Tool Calling | Score | Consistency | Attempt pass rate | Flaky tests | Tests Correct | Response Time (avg) | Input Tokens | Output Tokens | Reasoning Tokens |
|---|---|---|---|---|---|---|---|---|---|
| Seed-2.0-Code | 10.0 | 10.0 | 100.0% | 0 | 55.56s | 9,315 | 296 | 637 | |
| DeepSeek V4 Pro 0423 | 9.8 | 10.0 | 100.0% | 0 | 15.92s | 8,909 | 295 | 701 |
| Trivia | Score | Consistency | Attempt pass rate | Flaky tests | Tests Correct | Response Time (avg) | Input Tokens | Output Tokens | Reasoning Tokens |
|---|---|---|---|---|---|---|---|---|---|
| Seed-2.0-Code | 3.0 | 10.0 | 0.0% | 0 | 10.02s | 182 | 9 | 490 | |
| DeepSeek V4 Pro 0423 | 3.0 | 10.0 | 0.0% | 0 | 34.01s | 183 | 16 | 5,961 |
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