Model comparison
DeepSeek V3 vs SWE-1.7
Head-to-head evidence from 0 shared benchmark results across 0 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: DeepSeek V3 #147 (Supported); SWE-1.7 unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. DeepSeek V3 and SWE-1.7 share 0 comparable benchmark results. 0 of 8 categories are comparable. 22 results are unique to DeepSeek V3; 4 to SWE-1.7.
Updated July 18, 2026- Shared results
- 0
- DeepSeek V3 only
- 22
- SWE-1.7 only
- 4
- Comparable categories
- 0 / 8
Benchmark data for DeepSeek V3 and SWE-1.7 is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 0 shared benchmark results across 0 evidence categories; 0 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
BenchLM has partial data for these models, but not enough overlapping benchmark coverage to produce a fair score-level comparison yet.
SWE-1.7 has the larger context window at 256K, compared with 128K for DeepSeek V3.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | DeepSeek V3 | SWE-1.7 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | DeepSeek V3$0.27 input / $1.1 output | SWE-1.7Not available | A complete price comparison is not available. |
| Generation speedtokens per second | DeepSeek V3Not available | SWE-1.7Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | DeepSeek V3Not available | SWE-1.7Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | DeepSeek V3128K | SWE-1.7256K | SWE-1.7 lists the larger context window. |
Benchmark Deep Dive
Agentic5 benchmarks
Coding7 benchmarks
| Benchmark | DeepSeek V3 | SWE-1.7 | Result |
|---|---|---|---|
| LiveCodeBenchSource | 37.6% | — | Not comparable |
| SWE-bench VerifiedSource | 42% | — | Not comparable |
| AA Coding IndexSource | 23.0% | — | Not comparable |
| AA-SciCodeSource | 35.4% | — | Not comparable |
| FrontierCode 1.1 MainSource | — | 42.3% | Not comparable |
| Terminal-Bench 2.0Source | — | 81.5% | Not comparable |
| SWE MultilingualSource | — | 77.8% | Not comparable |
Reasoning2 benchmarks
Knowledge8 benchmarks
| Benchmark | DeepSeek V3 | SWE-1.7 | Result |
|---|---|---|---|
| GPQASource | 59.1% | — | Not comparable |
| MMLU-ProSource | 75.9% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 14.2% | — | Not comparable |
| AA-GPQA DiamondSource | 55.7% | — | Not comparable |
| AA-HLESource | 3.6% | — | Not comparable |
| AA-Omniscience IndexSource | -41.3% | — | Not comparable |
| AA-Omniscience AccuracySource | 25.4% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 89.4% | — | Not comparable |
Math1 benchmarks
| Benchmark | DeepSeek V3 | SWE-1.7 | Result |
|---|---|---|---|
| FrontierMath v2 (Tiers 1-3)Source | 1.724% | — | Not comparable |
Multimodal1 benchmarks
| Benchmark | DeepSeek V3 | SWE-1.7 | Result |
|---|---|---|---|
| Design Arena WebsiteSource | 1152 | — | Not comparable |
Frequently Asked Questions (3)
Can I compare DeepSeek V3 and SWE-1.7 on BenchLM yet?
Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still coming soon.
Why does this comparison show “coming soon”?
BenchLM only shows category winners and benchmark-level calls when we have sourced results that can be compared fairly. For these models, the public benchmark coverage is not complete enough yet.
What data is available for DeepSeek V3 and SWE-1.7 today?
DeepSeek V3: $0.27 input / $1.10 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
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