Pick Claude Sonnet 4.5 for agentic coding — 77.2% on swe-bench verified, the best score any model had posted at its launch or computer use and gui automation (61.4% osworld at launch). Pick DeepSeek V3.2 for long-context efficiency via deepseek sparse attention (dsa) or agentic tool-use with thinking integrated into tool calls (thinking/non-thinking modes). Choose DeepSeek V3.2 if you need self-hosting or data privacy; Claude Sonnet 4.5 if you want a managed API.
Claude Sonnet 4.5 (Anthropic, US) and DeepSeek V3.2 (DeepSeek, China) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. Claude Sonnet 4.5 is september 2025's coding state of the art at $3/$15 — still supported, but 200K-capped and twice superseded. DeepSeek V3.2 is a cost-efficient, open-weight (MIT) 685B-parameter MoE model whose DeepSeek Sparse Attention delivers GPT-5-comparable reasoning with far cheaper long-context inference. They diverge most on price, context window, open vs. closed weights and coding benchmarks — each quantified below from the models' real specs.
Key differences
Price: DeepSeek V3.2 is about 11× cheaper on input ($0.28/$0.42 per 1M tokens vs $3/$15 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
Context window: Claude Sonnet 4.5 holds 1.5× more — 200K (~300 pages) vs 131K (~197 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
Coding: Claude Sonnet 4.5 leads SWE-Bench Verified by 4.1 points (77.2% vs 73.1%) — a real edge on hard, real-world software tasks.
Recency: DeepSeek V3.2 is the newer model by about 2 months (released December 1, 2025), usually meaning fresher training data and capabilities.
Ecosystem: this is a US-vs-China matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Specifications
Spec
Claude Sonnet 4.5
DeepSeek V3.2
Provider
Anthropic (US)
DeepSeek (China)
Released
September 29, 2025
December 1, 2025
Context window
200K (~300 pages)
131K (~197 pages)
Price (in/out)
$3/$15 per 1M tokens
$0.28/$0.42 per 1M tokens
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image, code
text, code
SWE-Bench Verified
77.2%
73.1%
MRCR v2 @ 1M
Not published
Not published
Who wins what
Agentic coding — 77.2% on SWE-Bench Verified, the best score any model had posted at its launch: Claude Sonnet 4.5 — It scores 77.2% on SWE-Bench Verified against DeepSeek V3.2's 73.1% — a 4.1-point edge on real repository work.
Computer use and GUI automation (61.4% OSWorld at launch): Claude Sonnet 4.5 — September 2025's coding state of the art at $3/$15 — still supported, but 200K-capped and twice superseded — and it leads SWE-Bench Verified 77.2% to 73.1%.
Long-horizon autonomy — Anthropic reported 30+ hours of sustained focus on multi-step tasks: Claude Sonnet 4.5 — Its 200K window holds about 1.5× more than DeepSeek V3.2's 131K in a single prompt.
Long-context efficiency via DeepSeek Sparse Attention (DSA): DeepSeek V3.2 — A cost-efficient, open-weight (MIT) 685B-parameter MoE model whose DeepSeek Sparse Attention delivers GPT-5-comparable reasoning with far cheaper long-context inference — and it runs cheaper at $0.28/$0.42 per 1M tokens.
Agentic tool-use with thinking integrated into tool calls (thinking/non-thinking modes): DeepSeek V3.2 — Claude Sonnet 4.5 is comparatively weak here — missing the modern API surface: no adaptive thinking, no effort control, and half the max output of newer Sonnets
Elite competition math and reasoning (AIME 2025 93.1, Codeforces 2386): DeepSeek V3.2 — A cost-efficient, open-weight (MIT) 685B-parameter MoE model whose DeepSeek Sparse Attention delivers GPT-5-comparable reasoning with far cheaper long-context inference — and its weights are open while Claude Sonnet 4.5 is API-only.
Lowest cost at scale: DeepSeek V3.2 — At $0.28/$0.42 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input: Claude Sonnet 4.5 — Its 200K window is about 1.5× larger than DeepSeek V3.2's 131K, fitting roughly 300 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: DeepSeek V3.2 — At $0.28/$0.42 per 1M tokens it undercuts Claude Sonnet 4.5, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Claude Sonnet 4.5 — Larger 200K window fits more in one prompt.
A team with data-privacy or self-hosting needs: DeepSeek V3.2 — Open weights let you run it on your own hardware; Claude Sonnet 4.5 is API-only.
Anyone whose priority is agentic coding — 77.2% on swe-bench verified, the best score any model had posted at its launch: Claude Sonnet 4.5 — It is specifically built for that.
Anyone whose priority is long-context efficiency via deepseek sparse attention (dsa): DeepSeek V3.2 — That is its strongest area.
An enterprise with regional data-residency rules: Claude Sonnet 4.5 or DeepSeek V3.2 — Origin (US vs China) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
Claude Sonnet 4.5: where it fits
September 2025's coding state of the art at $3/$15 — still supported, but 200K-capped and twice superseded. Released September 29, 2025 by Anthropic, it is built for agentic coding — 77.2% on SWE-Bench Verified, the best score any model had posted at its launch, computer use and GUI automation (61.4% OSWorld at launch), long-horizon autonomy — Anthropic reported 30+ hours of sustained focus on multi-step tasks, and tracking its own remaining token budget natively, which few models do.
Its trade-offs are real: superseded twice — Sonnet 4.6 and Sonnet 5 match or beat it at the same or lower price, capped at 200K since Anthropic retired its 1M beta in April 2026, while its successors ship 1M as standard, and missing the modern API surface: no adaptive thinking, no effort control, and half the max output of newer Sonnets. At $3 in / $15 out per million tokens, it sits in the mid price band.
DeepSeek V3.2: where it fits
A cost-efficient, open-weight (MIT) 685B-parameter MoE model whose DeepSeek Sparse Attention delivers GPT-5-comparable reasoning with far cheaper long-context inference. Released December 1, 2025 by DeepSeek, it is built for long-context efficiency via DeepSeek Sparse Attention (DSA), agentic tool-use with thinking integrated into tool calls (thinking/non-thinking modes), elite competition math and reasoning (AIME 2025 93.1, Codeforces 2386), and low-cost, open-weight (MIT) self-hosting.
Its trade-offs: text-only — no image, audio, or video input, and sWE-Bench Verified (73.1) trails the top closed coding models (Claude 4.5 Sonnet 77.2, Gemini 3 Pro 76.2). At $0.28 in / $0.42 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
The defining split here is open vs. closed. DeepSeek V3.2 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Claude Sonnet 4.5 gives you a managed, always-updated API with no infrastructure to run. Teams with GPUs, privacy requirements, or huge volume often favour the open model; teams that want zero ops and the latest capabilities favour the closed one. Capability is close enough that this operational question, not the benchmark, usually decides it.
Frequently asked questions
Is Claude Sonnet 4.5 or DeepSeek V3.2 better for coding?
On SWE-Bench Verified, Claude Sonnet 4.5 scores 77.2% and DeepSeek V3.2 scores 73.1% — Claude Sonnet 4.5 has the measurable edge.
Which is cheaper, Claude Sonnet 4.5 or DeepSeek V3.2?
DeepSeek V3.2 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Claude Sonnet 4.5 is API-metered at $3/$15 per 1M tokens. For most teams without GPUs, the API model is cheaper to start; at very high volume, self-hosting can win.
Which has the bigger context window?
Claude Sonnet 4.5 — 200K vs 131K, about 1.5× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Claude Sonnet 4.5 and DeepSeek V3.2 together?
Yes — a multi-model platform like LumiChats gives you Claude Sonnet 4.5, DeepSeek V3.2 and 40+ others under one ₹69/day pass (about $1/day), so you can draft with one and cross-check with the other instead of buying two subscriptions.
Which is newer, Claude Sonnet 4.5 or DeepSeek V3.2?
DeepSeek V3.2 — released December 1, 2025, about 2 months after Claude Sonnet 4.5.
Claude Sonnet 4.5 vs DeepSeek V3.2
Anthropic · US | DeepSeek · China · Updated June 2026
Quick verdict
Pick Claude Sonnet 4.5 for agentic coding — 77.2% on swe-bench verified, the best score any model had posted at its launch or computer use and gui automation (61.4% osworld at launch). Pick DeepSeek V3.2 for long-context efficiency via deepseek sparse attention (dsa) or agentic tool-use with thinking integrated into tool calls (thinking/non-thinking modes). Choose DeepSeek V3.2 if you need self-hosting or data privacy; Claude Sonnet 4.5 if you want a managed API.
Claude Sonnet 4.5 (Anthropic, US) and DeepSeek V3.2 (DeepSeek, China) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. Claude Sonnet 4.5 is september 2025's coding state of the art at $3/$15 — still supported, but 200K-capped and twice superseded. DeepSeek V3.2 is a cost-efficient, open-weight (MIT) 685B-parameter MoE model whose DeepSeek Sparse Attention delivers GPT-5-comparable reasoning with far cheaper long-context inference. They diverge most on price, context window, open vs. closed weights and coding benchmarks — each quantified below from the models' real specs.
Key differences at a glance
▸Price: DeepSeek V3.2 is about 11× cheaper on input ($0.28/$0.42 per 1M tokens vs $3/$15 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
▸Context window: Claude Sonnet 4.5 holds 1.5× more — 200K (~300 pages) vs 131K (~197 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
▸Coding: Claude Sonnet 4.5 leads SWE-Bench Verified by 4.1 points (77.2% vs 73.1%) — a real edge on hard, real-world software tasks.
▸Recency: DeepSeek V3.2 is the newer model by about 2 months (released December 1, 2025), usually meaning fresher training data and capabilities.
▸Ecosystem: this is a US-vs-China matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Side-by-side specs
Spec
Claude Sonnet 4.5
DeepSeek V3.2
Provider
Anthropic (US)
DeepSeek (China)
Released
September 29, 2025
December 1, 2025
Context window
200K (~300 pages)
131K (~197 pages)
Price (in/out)
$3/$15 per 1M tokens
$0.28/$0.42 per 1M tokens
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image, code
text, code
SWE-Bench Verified
77.2%
73.1%
MRCR v2 @ 1M
Not published
Not published
Who wins what
Agentic coding — 77.2% on SWE-Bench Verified, the best score any model had posted at its launch
Claude Sonnet 4.5
It scores 77.2% on SWE-Bench Verified against DeepSeek V3.2's 73.1% — a 4.1-point edge on real repository work.
Computer use and GUI automation (61.4% OSWorld at launch)
Claude Sonnet 4.5
September 2025's coding state of the art at $3/$15 — still supported, but 200K-capped and twice superseded — and it leads SWE-Bench Verified 77.2% to 73.1%.
Long-horizon autonomy — Anthropic reported 30+ hours of sustained focus on multi-step tasks
Claude Sonnet 4.5
Its 200K window holds about 1.5× more than DeepSeek V3.2's 131K in a single prompt.
Long-context efficiency via DeepSeek Sparse Attention (DSA)
DeepSeek V3.2
A cost-efficient, open-weight (MIT) 685B-parameter MoE model whose DeepSeek Sparse Attention delivers GPT-5-comparable reasoning with far cheaper long-context inference — and it runs cheaper at $0.28/$0.42 per 1M tokens.
Agentic tool-use with thinking integrated into tool calls (thinking/non-thinking modes)
DeepSeek V3.2
Claude Sonnet 4.5 is comparatively weak here — missing the modern API surface: no adaptive thinking, no effort control, and half the max output of newer Sonnets
Elite competition math and reasoning (AIME 2025 93.1, Codeforces 2386)
DeepSeek V3.2
A cost-efficient, open-weight (MIT) 685B-parameter MoE model whose DeepSeek Sparse Attention delivers GPT-5-comparable reasoning with far cheaper long-context inference — and its weights are open while Claude Sonnet 4.5 is API-only.
Lowest cost at scale
DeepSeek V3.2
At $0.28/$0.42 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
Claude Sonnet 4.5
Its 200K window is about 1.5× larger than DeepSeek V3.2's 131K, fitting roughly 300 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ DeepSeek V3.2
At $0.28/$0.42 per 1M tokens it undercuts Claude Sonnet 4.5, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Claude Sonnet 4.5
Larger 200K window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ DeepSeek V3.2
Open weights let you run it on your own hardware; Claude Sonnet 4.5 is API-only.
Anyone whose priority is agentic coding — 77.2% on swe-bench verified, the best score any model had posted at its launch
→ Claude Sonnet 4.5
It is specifically built for that.
Anyone whose priority is long-context efficiency via deepseek sparse attention (dsa)
→ DeepSeek V3.2
That is its strongest area.
An enterprise with regional data-residency rules
→ Claude Sonnet 4.5 or DeepSeek V3.2
Origin (US vs China) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
Claude Sonnet 4.5: where it fits
September 2025's coding state of the art at $3/$15 — still supported, but 200K-capped and twice superseded. Released September 29, 2025 by Anthropic, it is built for agentic coding — 77.2% on SWE-Bench Verified, the best score any model had posted at its launch, computer use and GUI automation (61.4% OSWorld at launch), long-horizon autonomy — Anthropic reported 30+ hours of sustained focus on multi-step tasks, and tracking its own remaining token budget natively, which few models do.
Its trade-offs are real: superseded twice — Sonnet 4.6 and Sonnet 5 match or beat it at the same or lower price, capped at 200K since Anthropic retired its 1M beta in April 2026, while its successors ship 1M as standard, and missing the modern API surface: no adaptive thinking, no effort control, and half the max output of newer Sonnets. At $3 in / $15 out per million tokens, it sits in the mid price band.
DeepSeek V3.2: where it fits
A cost-efficient, open-weight (MIT) 685B-parameter MoE model whose DeepSeek Sparse Attention delivers GPT-5-comparable reasoning with far cheaper long-context inference. Released December 1, 2025 by DeepSeek, it is built for long-context efficiency via DeepSeek Sparse Attention (DSA), agentic tool-use with thinking integrated into tool calls (thinking/non-thinking modes), elite competition math and reasoning (AIME 2025 93.1, Codeforces 2386), and low-cost, open-weight (MIT) self-hosting.
Its trade-offs: text-only — no image, audio, or video input, and sWE-Bench Verified (73.1) trails the top closed coding models (Claude 4.5 Sonnet 77.2, Gemini 3 Pro 76.2). At $0.28 in / $0.42 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
The defining split here is open vs. closed. DeepSeek V3.2 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Claude Sonnet 4.5 gives you a managed, always-updated API with no infrastructure to run. Teams with GPUs, privacy requirements, or huge volume often favour the open model; teams that want zero ops and the latest capabilities favour the closed one. Capability is close enough that this operational question, not the benchmark, usually decides it.
Want both Claude Sonnet 4.5 and DeepSeek V3.2 without two subscriptions? LumiChats gives you these plus 40+ models under one ₹69/day pass (about $1/day) — draft with one, cross-check with the other.
Is Claude Sonnet 4.5 or DeepSeek V3.2 better for coding?
On SWE-Bench Verified, Claude Sonnet 4.5 scores 77.2% and DeepSeek V3.2 scores 73.1% — Claude Sonnet 4.5 has the measurable edge.
Which is cheaper, Claude Sonnet 4.5 or DeepSeek V3.2?
DeepSeek V3.2 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Claude Sonnet 4.5 is API-metered at $3/$15 per 1M tokens. For most teams without GPUs, the API model is cheaper to start; at very high volume, self-hosting can win.
Which has the bigger context window?
Claude Sonnet 4.5 — 200K vs 131K, about 1.5× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Claude Sonnet 4.5 and DeepSeek V3.2 together?
Yes — a multi-model platform like LumiChats gives you Claude Sonnet 4.5, DeepSeek V3.2 and 40+ others under one ₹69/day pass (about $1/day), so you can draft with one and cross-check with the other instead of buying two subscriptions.
Which is newer, Claude Sonnet 4.5 or DeepSeek V3.2?
DeepSeek V3.2 — released December 1, 2025, about 2 months after Claude Sonnet 4.5.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.