Model comparison
Claude Haiku 4.5 vs DeepSeek V3.2
Head-to-head evidence from 3 shared benchmark results across 2 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Claude Haiku 4.5 #77 (Estimated); DeepSeek V3.2 #82 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Claude Haiku 4.5 and DeepSeek V3.2 share 3 comparable benchmark results. 2 of 8 categories are comparable. 2 results are unique to Claude Haiku 4.5; 16 to DeepSeek V3.2.
Updated July 20, 2026- Shared results
- 3
- Claude Haiku 4.5 only
- 2
- DeepSeek V3.2 only
- 16
- Comparable categories
- 2 / 8
Pick Claude Haiku 4.5 if you want the stronger benchmark profile. DeepSeek V3.2 only becomes the better choice if mathematics is the priority or you want the cheaper token bill.
Confidence note. This is a partial-evidence comparison with 3 shared benchmark results across 2 evidence categories; 2 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
Claude Haiku 4.5 has the cleaner BenchAlign overall profile here, landing at 56.58 versus 55.4. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
Claude Haiku 4.5's sharpest advantage is in coding, where it averages 73.3 against 60.9. The single biggest benchmark swing on the page is FrontierMath v2 (Tiers 1-3), 5.903% to 22.100%. DeepSeek V3.2 does hit back in mathematics, so the answer changes if that is the part of the workload you care about most.
Claude Haiku 4.5 is also the more expensive model on tokens at $1.00 input / $5.00 output per 1M tokens, versus $0.28 input / $0.42 output per 1M tokens for DeepSeek V3.2. That is roughly 11.9x on output cost alone. Claude Haiku 4.5 gives you the larger context window at 200K, compared with 128K for DeepSeek V3.2.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
| Category | Claude Haiku 4.5 | Δ | DeepSeek V3.2 |
|---|---|---|---|
| Coding | Claude Haiku 4.573.3 | Margin← 12.4 | DeepSeek V3.260.9 |
| Math | Claude Haiku 4.54.9 | Margin→ 12.2 | DeepSeek V3.217.1 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
FrontierMath v2 (Tiers 1-3)
MathA 5.903%B 22.100%Winner: DeepSeek V3.2Δ 16.2FrontierMath v2 (Tiers 1-3): Claude Haiku 4.5 scored 5.903%; DeepSeek V3.2 scored 22.100%. DeepSeek V3.2 wins this benchmark. - Source ↗
FrontierMath v2 (Tier 4)
MathA 2.083%B 2.100%Winner: DeepSeek V3.2Δ 0FrontierMath v2 (Tier 4): Claude Haiku 4.5 scored 2.083%; DeepSeek V3.2 scored 2.100%. DeepSeek V3.2 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Claude Haiku 4.5 | DeepSeek V3.2 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Claude Haiku 4.5$1 input / $5 output | DeepSeek V3.2$0.28 input / $0.42 output | DeepSeek V3.2 has the lower combined listed price. |
| Generation speedtokens per second | Claude Haiku 4.5Not available | DeepSeek V3.235 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Claude Haiku 4.5Not available | DeepSeek V3.23.75 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Claude Haiku 4.5200K | DeepSeek V3.2128K | Claude Haiku 4.5 lists the larger context window. |
Benchmark Deep Dive
Agentic5 benchmarks
CodingClaude Haiku 4.5 wins4 benchmarks
Reasoning2 benchmarks
Knowledge6 benchmarks
| Benchmark | Claude Haiku 4.5 | DeepSeek V3.2 | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | — | 24.7% | Not comparable |
| AA-GPQA DiamondSource | — | 75.1% | Not comparable |
| AA-HLESource | — | 10.5% | Not comparable |
| AA-Omniscience IndexSource | — | -46.7% | Not comparable |
| AA-Omniscience AccuracySource | — | 24.2% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 93.5% | Not comparable |
MathDeepSeek V3.2 wins2 benchmarks
Multimodal1 benchmarks
| Benchmark | Claude Haiku 4.5 | DeepSeek V3.2 | Result |
|---|---|---|---|
| Design Arena WebsiteSource | 1154 | 1206 | DeepSeek V3.2 leads |
Inst. Following1 benchmarks
| Benchmark | Claude Haiku 4.5 | DeepSeek V3.2 | Result |
|---|---|---|---|
| AA-IFBenchSource | — | 49.0% | Not comparable |
Frequently Asked Questions (3)
Which is better, Claude Haiku 4.5 or DeepSeek V3.2?
Claude Haiku 4.5 is ahead on BenchLM's BenchAlign leaderboard, 56.58 to 55.4. The biggest single separator in this matchup is FrontierMath v2 (Tiers 1-3), where the scores are 5.903% and 22.100%.
Which is better for coding, Claude Haiku 4.5 or DeepSeek V3.2?
Claude Haiku 4.5 has the edge for coding in this comparison, averaging 73.3 versus 60.9. DeepSeek V3.2 stays close enough that the answer can still flip depending on your workload.
Which is better for math, Claude Haiku 4.5 or DeepSeek V3.2?
DeepSeek V3.2 has the edge for math in this comparison, averaging 17.1 versus 4.9. Inside this category, FrontierMath v2 (Tiers 1-3) is the benchmark that creates the most daylight between them.
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