Pick DeepSeek V4 for near-frontier coding at ~1/12 the cost or open mit-licensed weights you can self-host. Pick GPT-5.6 Luna for cheapest gpt-5.6 tier for high-volume drafting and automation or fast, affordable execution while keeping respectable coding. Choose DeepSeek V4 if you need self-hosting or data privacy; GPT-5.6 Luna if you want a managed API.
DeepSeek V4 (DeepSeek, China) and GPT-5.6 Luna (OpenAI, US) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. DeepSeek V4 is china's open-weight price earthquake — near-frontier capability at roughly a twelfth of GPT-5.5's cost. GPT-5.6 Luna is the budget, high-throughput GPT-5.6 tier — built for cheap, fast, large-volume work rather than deep long-context reasoning. They diverge most on price and open vs. closed weights — each quantified below from the models' real specs.
Key differences
Price: DeepSeek V4 is about 2.3× cheaper on input ($0.435/$0.87 per 1M tokens vs $1/$6 per 1M tokens) — meaningful once you are processing millions of tokens a month.
Context window: both advertise 1M (~1,500 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
Recency: GPT-5.6 Luna is the newer model by about 3 months (released July 9, 2026), usually meaning fresher training data and capabilities.
Ecosystem: this is a China-vs-US matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Specifications
Spec
DeepSeek V4
GPT-5.6 Luna
Provider
DeepSeek (China)
OpenAI (US)
Released
April 24, 2026
July 9, 2026
Context window
1M (~1,500 pages)
1M (~1,500 pages)
Price (in/out)
$0.435/$0.87 per 1M tokens
$1/$6 per 1M tokens
Open weight?
Yes — self-hostable
No — API only
Modalities
text, code
text, image, code
SWE-Bench Verified
80.6%
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Near-frontier coding at ~1/12 the cost: DeepSeek V4 — A core design strength of DeepSeek V4.
Open MIT-licensed weights you can self-host: DeepSeek V4 — A core design strength of DeepSeek V4.
No long-context surcharge: DeepSeek V4 — A core design strength of DeepSeek V4.
Cheapest GPT-5.6 tier for high-volume drafting and automation: GPT-5.6 Luna — A core design strength of GPT-5.6 Luna.
Fast, affordable execution while keeping respectable coding: GPT-5.6 Luna — A core design strength of GPT-5.6 Luna.
Same 1M context and programmatic tool calling as its siblings: GPT-5.6 Luna — A core design strength of GPT-5.6 Luna.
Lowest cost at scale: DeepSeek V4 — At $0.435/$0.87 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Which should you pick?
A cost-sensitive startup shipping high volume: DeepSeek V4 — At $0.435/$0.87 per 1M tokens it undercuts GPT-5.6 Luna, and on millions of tokens that margin decides the monthly bill.
A team with data-privacy or self-hosting needs: DeepSeek V4 — Open weights let you run it on your own hardware; GPT-5.6 Luna is API-only.
Anyone whose priority is near-frontier coding at ~1/12 the cost: DeepSeek V4 — It is specifically built for that.
Anyone whose priority is cheapest gpt-5.6 tier for high-volume drafting and automation: GPT-5.6 Luna — That is its strongest area.
An enterprise with regional data-residency rules: GPT-5.6 Luna or DeepSeek V4 — Origin (China vs US) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
DeepSeek V4: where it fits
China's open-weight price earthquake — near-frontier capability at roughly a twelfth of GPT-5.5's cost. Released April 24, 2026 by DeepSeek, it is built for near-frontier coding at ~1/12 the cost, open MIT-licensed weights you can self-host, no long-context surcharge, and highest LiveCodeBench result.
Its trade-offs are real: trails the very best on hardest agentic coding, and text/code focused, less multimodal. At $0.435 in / $0.87 out per million tokens, it sits in the budget price band.
GPT-5.6 Luna: where it fits
The budget, high-throughput GPT-5.6 tier — built for cheap, fast, large-volume work rather than deep long-context reasoning. Released July 9, 2026 by OpenAI, it is built for cheapest GPT-5.6 tier for high-volume drafting and automation, fast, affordable execution while keeping respectable coding, same 1M context and programmatic tool calling as its siblings, and high-throughput simple agentic jobs.
Its trade-offs: weak long-context recall deep in its 1M window (MRCR far below Sol), and lowest raw capability of the three GPT-5.6 tiers; no open weights. At $1 in / $6 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 V4 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. GPT-5.6 Luna 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 DeepSeek V4 or GPT-5.6 Luna better for coding?
Public SWE-Bench figures are not available for GPT-5.6 Luna, so the honest test is your own repository — run an identical real bug through both. By design, DeepSeek V4 leans toward near-frontier coding at ~1/12 the cost while GPT-5.6 Luna leans toward cheapest gpt-5.6 tier for high-volume drafting and automation, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, DeepSeek V4 or GPT-5.6 Luna?
DeepSeek V4 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while GPT-5.6 Luna is API-metered at $1/$6 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?
Both advertise 1M (~1,500 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both DeepSeek V4 and GPT-5.6 Luna together?
Yes — a multi-model platform like LumiChats gives you DeepSeek V4, GPT-5.6 Luna 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, DeepSeek V4 or GPT-5.6 Luna?
GPT-5.6 Luna — released July 9, 2026, about 3 months after DeepSeek V4.
DeepSeek V4 vs GPT-5.6 Luna
DeepSeek · China | OpenAI · US · Updated June 2026
Quick verdict
Pick DeepSeek V4 for near-frontier coding at ~1/12 the cost or open mit-licensed weights you can self-host. Pick GPT-5.6 Luna for cheapest gpt-5.6 tier for high-volume drafting and automation or fast, affordable execution while keeping respectable coding. Choose DeepSeek V4 if you need self-hosting or data privacy; GPT-5.6 Luna if you want a managed API.
DeepSeek V4 (DeepSeek, China) and GPT-5.6 Luna (OpenAI, US) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. DeepSeek V4 is china's open-weight price earthquake — near-frontier capability at roughly a twelfth of GPT-5.5's cost. GPT-5.6 Luna is the budget, high-throughput GPT-5.6 tier — built for cheap, fast, large-volume work rather than deep long-context reasoning. They diverge most on price and open vs. closed weights — each quantified below from the models' real specs.
Key differences at a glance
▸Price: DeepSeek V4 is about 2.3× cheaper on input ($0.435/$0.87 per 1M tokens vs $1/$6 per 1M tokens) — meaningful once you are processing millions of tokens a month.
▸Context window: both advertise 1M (~1,500 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
▸Recency: GPT-5.6 Luna is the newer model by about 3 months (released July 9, 2026), usually meaning fresher training data and capabilities.
▸Ecosystem: this is a China-vs-US matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Side-by-side specs
Spec
DeepSeek V4
GPT-5.6 Luna
Provider
DeepSeek (China)
OpenAI (US)
Released
April 24, 2026
July 9, 2026
Context window
1M (~1,500 pages)
1M (~1,500 pages)
Price (in/out)
$0.435/$0.87 per 1M tokens
$1/$6 per 1M tokens
Open weight?
Yes — self-hostable
No — API only
Modalities
text, code
text, image, code
SWE-Bench Verified
80.6%
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Near-frontier coding at ~1/12 the cost
DeepSeek V4
A core design strength of DeepSeek V4.
Open MIT-licensed weights you can self-host
DeepSeek V4
A core design strength of DeepSeek V4.
No long-context surcharge
DeepSeek V4
A core design strength of DeepSeek V4.
Cheapest GPT-5.6 tier for high-volume drafting and automation
GPT-5.6 Luna
A core design strength of GPT-5.6 Luna.
Fast, affordable execution while keeping respectable coding
GPT-5.6 Luna
A core design strength of GPT-5.6 Luna.
Same 1M context and programmatic tool calling as its siblings
GPT-5.6 Luna
A core design strength of GPT-5.6 Luna.
Lowest cost at scale
DeepSeek V4
At $0.435/$0.87 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Which should you pick?
A cost-sensitive startup shipping high volume
→ DeepSeek V4
At $0.435/$0.87 per 1M tokens it undercuts GPT-5.6 Luna, and on millions of tokens that margin decides the monthly bill.
A team with data-privacy or self-hosting needs
→ DeepSeek V4
Open weights let you run it on your own hardware; GPT-5.6 Luna is API-only.
Anyone whose priority is near-frontier coding at ~1/12 the cost
→ DeepSeek V4
It is specifically built for that.
Anyone whose priority is cheapest gpt-5.6 tier for high-volume drafting and automation
→ GPT-5.6 Luna
That is its strongest area.
An enterprise with regional data-residency rules
→ GPT-5.6 Luna or DeepSeek V4
Origin (China vs US) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
DeepSeek V4: where it fits
China's open-weight price earthquake — near-frontier capability at roughly a twelfth of GPT-5.5's cost. Released April 24, 2026 by DeepSeek, it is built for near-frontier coding at ~1/12 the cost, open MIT-licensed weights you can self-host, no long-context surcharge, and highest LiveCodeBench result.
Its trade-offs are real: trails the very best on hardest agentic coding, and text/code focused, less multimodal. At $0.435 in / $0.87 out per million tokens, it sits in the budget price band.
GPT-5.6 Luna: where it fits
The budget, high-throughput GPT-5.6 tier — built for cheap, fast, large-volume work rather than deep long-context reasoning. Released July 9, 2026 by OpenAI, it is built for cheapest GPT-5.6 tier for high-volume drafting and automation, fast, affordable execution while keeping respectable coding, same 1M context and programmatic tool calling as its siblings, and high-throughput simple agentic jobs.
Its trade-offs: weak long-context recall deep in its 1M window (MRCR far below Sol), and lowest raw capability of the three GPT-5.6 tiers; no open weights. At $1 in / $6 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 V4 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. GPT-5.6 Luna 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 DeepSeek V4 and GPT-5.6 Luna 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.
Public SWE-Bench figures are not available for GPT-5.6 Luna, so the honest test is your own repository — run an identical real bug through both. By design, DeepSeek V4 leans toward near-frontier coding at ~1/12 the cost while GPT-5.6 Luna leans toward cheapest gpt-5.6 tier for high-volume drafting and automation, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, DeepSeek V4 or GPT-5.6 Luna?
DeepSeek V4 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while GPT-5.6 Luna is API-metered at $1/$6 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?
Both advertise 1M (~1,500 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both DeepSeek V4 and GPT-5.6 Luna together?
Yes — a multi-model platform like LumiChats gives you DeepSeek V4, GPT-5.6 Luna 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, DeepSeek V4 or GPT-5.6 Luna?
GPT-5.6 Luna — released July 9, 2026, about 3 months after DeepSeek V4.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.