Pick DeepSeek V4 for near-frontier coding at ~1/12 the cost or open mit-licensed weights you can self-host. Pick GPT-6 Luna for openai's cheapest gpt-6 tier — $0.10/$0.50 per million tokens, optimized for fast responses at high volume or available to free and go plan users in the chatgpt desktop app, not gated to paid tiers. Choose DeepSeek V4 if you need self-hosting or data privacy; GPT-6 Luna if you want a managed API.
DeepSeek V4 (DeepSeek, China) and GPT-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-6 Luna is openAI's cheapest GPT-6 tier, released September 22, 2026 alongside GPT-6 Sol — $0.10/$0.50 per million tokens, built for speed over depth. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences
Price: GPT-6 Luna is about 6.6× cheaper on input ($0.1/$0.5 per 1M tokens vs $0.66/$1.98 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
Context window: 1M vs 1.05M tokens — within a few percent of each other, so treat this as a tie and test on your own long inputs, since usable recall varies by model.
Recency: GPT-6 Luna is the newer model by about 5 months (released September 22, 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-6 Luna
Provider
DeepSeek (China)
OpenAI (US)
Released
April 24, 2026
September 22, 2026
Context window
1M (~1,500 pages)
1.05M tokens (~1,575 pages)
Price (in/out)
$0.66/$1.98 per 1M tokens
$0.1/$0.5 per 1M tokens
Open weight?
Yes — self-hostable
No — API only
Modalities
text, code
text, image
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 — China's open-weight price earthquake — near-frontier capability at roughly a twelfth of GPT-5.5's cost — and its weights are open while GPT-6 Luna is API-only.
Open MIT-licensed weights you can self-host: DeepSeek V4 — Open weights make this possible at all — GPT-6 Luna is API-only, so it cannot leave the vendor's servers.
No long-context surcharge: DeepSeek V4 — DeepSeek V4 lists no long-context surcharge among its strengths; GPT-6 Luna does not.
OpenAI's cheapest GPT-6 tier — $0.10/$0.50 per million tokens, optimized for fast responses at high volume: GPT-6 Luna — At $0.1/$0.5 per 1M tokens it undercuts DeepSeek V4 ($0.66/$1.98 per 1M tokens), and that gap compounds at volume.
Available to Free and Go plan users in the ChatGPT desktop app, not gated to paid tiers: GPT-6 Luna — DeepSeek V4 is comparatively weak here — this generic 'V4' entry mirrors DeepSeek V4-Pro's specs - see DeepSeek V4-Pro and DeepSeek V4-Flash for DeepSeek's actual named product tiers
Cache reads at $0.01/MTok — a 90% discount, the cheapest in the GPT-6 family: GPT-6 Luna — OpenAI's cheapest GPT-6 tier, released September 22, 2026 alongside GPT-6 Sol — $0.10/$0.50 per million tokens, built for speed over depth — and it runs cheaper at $0.1/$0.5 per 1M tokens.
Lowest cost at scale: GPT-6 Luna — At $0.1/$0.5 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: GPT-6 Luna — At $0.1/$0.5 per 1M tokens it undercuts DeepSeek V4, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: GPT-6 Luna — Larger 1.05M tokens window fits more in one prompt.
A team with data-privacy or self-hosting needs: DeepSeek V4 — Open weights let you run it on your own hardware; GPT-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 openai's cheapest gpt-6 tier — $0.10/$0.50 per million tokens, optimized for fast responses at high volume: GPT-6 Luna — That is its strongest area.
An enterprise with regional data-residency rules: GPT-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: this generic 'V4' entry mirrors DeepSeek V4-Pro's specs - see DeepSeek V4-Pro and DeepSeek V4-Flash for DeepSeek's actual named product tiers, trails the very best on hardest agentic coding, and text/code focused, less multimodal. At $0.66 in / $1.98 out per million tokens, it sits in the budget price band.
GPT-6 Luna: where it fits
OpenAI's cheapest GPT-6 tier, released September 22, 2026 alongside GPT-6 Sol — $0.10/$0.50 per million tokens, built for speed over depth. Released September 22, 2026 by OpenAI, it is built for openAI's cheapest GPT-6 tier — $0.10/$0.50 per million tokens, optimized for fast responses at high volume, available to Free and Go plan users in the ChatGPT desktop app, not gated to paid tiers, cache reads at $0.01/MTok — a 90% discount, the cheapest in the GPT-6 family, and 1.05M-token context window carried down from the flagship tier.
Its trade-offs: less reasoning capability than sibling GPT-6 Sol — built for speed and volume, not hard problems, and as the entry-level tier, expect it to be the first model swapped out when OpenAI ships the next cost-tier refresh. At $0.1 in / $0.5 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-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-6 Luna better for coding?
Public SWE-Bench figures are not available for GPT-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-6 Luna leans toward openai's cheapest gpt-6 tier — $0.10/$0.50 per million tokens, optimized for fast responses at high volume, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, DeepSeek V4 or GPT-6 Luna?
DeepSeek V4 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while GPT-6 Luna is API-metered at $0.1/$0.5 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?
Effectively neither — 1M vs 1.05M tokens is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both DeepSeek V4 and GPT-6 Luna together?
Yes — a multi-model platform like LumiChats gives you DeepSeek V4, GPT-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-6 Luna?
GPT-6 Luna — released September 22, 2026, about 5 months after DeepSeek V4.
DeepSeek V4 vs GPT-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-6 Luna for openai's cheapest gpt-6 tier — $0.10/$0.50 per million tokens, optimized for fast responses at high volume or available to free and go plan users in the chatgpt desktop app, not gated to paid tiers. Choose DeepSeek V4 if you need self-hosting or data privacy; GPT-6 Luna if you want a managed API.
DeepSeek V4 (DeepSeek, China) and GPT-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-6 Luna is openAI's cheapest GPT-6 tier, released September 22, 2026 alongside GPT-6 Sol — $0.10/$0.50 per million tokens, built for speed over depth. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences at a glance
▸Price: GPT-6 Luna is about 6.6× cheaper on input ($0.1/$0.5 per 1M tokens vs $0.66/$1.98 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
▸Context window: 1M vs 1.05M tokens — within a few percent of each other, so treat this as a tie and test on your own long inputs, since usable recall varies by model.
▸Recency: GPT-6 Luna is the newer model by about 5 months (released September 22, 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-6 Luna
Provider
DeepSeek (China)
OpenAI (US)
Released
April 24, 2026
September 22, 2026
Context window
1M (~1,500 pages)
1.05M tokens (~1,575 pages)
Price (in/out)
$0.66/$1.98 per 1M tokens
$0.1/$0.5 per 1M tokens
Open weight?
Yes — self-hostable
No — API only
Modalities
text, code
text, image
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
China's open-weight price earthquake — near-frontier capability at roughly a twelfth of GPT-5.5's cost — and its weights are open while GPT-6 Luna is API-only.
Open MIT-licensed weights you can self-host
DeepSeek V4
Open weights make this possible at all — GPT-6 Luna is API-only, so it cannot leave the vendor's servers.
No long-context surcharge
DeepSeek V4
DeepSeek V4 lists no long-context surcharge among its strengths; GPT-6 Luna does not.
OpenAI's cheapest GPT-6 tier — $0.10/$0.50 per million tokens, optimized for fast responses at high volume
GPT-6 Luna
At $0.1/$0.5 per 1M tokens it undercuts DeepSeek V4 ($0.66/$1.98 per 1M tokens), and that gap compounds at volume.
Available to Free and Go plan users in the ChatGPT desktop app, not gated to paid tiers
GPT-6 Luna
DeepSeek V4 is comparatively weak here — this generic 'V4' entry mirrors DeepSeek V4-Pro's specs - see DeepSeek V4-Pro and DeepSeek V4-Flash for DeepSeek's actual named product tiers
Cache reads at $0.01/MTok — a 90% discount, the cheapest in the GPT-6 family
GPT-6 Luna
OpenAI's cheapest GPT-6 tier, released September 22, 2026 alongside GPT-6 Sol — $0.10/$0.50 per million tokens, built for speed over depth — and it runs cheaper at $0.1/$0.5 per 1M tokens.
Lowest cost at scale
GPT-6 Luna
At $0.1/$0.5 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
→ GPT-6 Luna
At $0.1/$0.5 per 1M tokens it undercuts DeepSeek V4, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ GPT-6 Luna
Larger 1.05M tokens window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ DeepSeek V4
Open weights let you run it on your own hardware; GPT-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 openai's cheapest gpt-6 tier — $0.10/$0.50 per million tokens, optimized for fast responses at high volume
→ GPT-6 Luna
That is its strongest area.
An enterprise with regional data-residency rules
→ GPT-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: this generic 'V4' entry mirrors DeepSeek V4-Pro's specs - see DeepSeek V4-Pro and DeepSeek V4-Flash for DeepSeek's actual named product tiers, trails the very best on hardest agentic coding, and text/code focused, less multimodal. At $0.66 in / $1.98 out per million tokens, it sits in the budget price band.
GPT-6 Luna: where it fits
OpenAI's cheapest GPT-6 tier, released September 22, 2026 alongside GPT-6 Sol — $0.10/$0.50 per million tokens, built for speed over depth. Released September 22, 2026 by OpenAI, it is built for openAI's cheapest GPT-6 tier — $0.10/$0.50 per million tokens, optimized for fast responses at high volume, available to Free and Go plan users in the ChatGPT desktop app, not gated to paid tiers, cache reads at $0.01/MTok — a 90% discount, the cheapest in the GPT-6 family, and 1.05M-token context window carried down from the flagship tier.
Its trade-offs: less reasoning capability than sibling GPT-6 Sol — built for speed and volume, not hard problems, and as the entry-level tier, expect it to be the first model swapped out when OpenAI ships the next cost-tier refresh. At $0.1 in / $0.5 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-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-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-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-6 Luna leans toward openai's cheapest gpt-6 tier — $0.10/$0.50 per million tokens, optimized for fast responses at high volume, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, DeepSeek V4 or GPT-6 Luna?
DeepSeek V4 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while GPT-6 Luna is API-metered at $0.1/$0.5 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?
Effectively neither — 1M vs 1.05M tokens is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both DeepSeek V4 and GPT-6 Luna together?
Yes — a multi-model platform like LumiChats gives you DeepSeek V4, GPT-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-6 Luna?
GPT-6 Luna — released September 22, 2026, about 5 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.