Pick DeepSeek V4 for near-frontier coding at ~1/12 the cost or open mit-licensed weights you can self-host. Pick MiniMax M2.7 for agentic and terminal coding well above its price tier (57.0 on terminal-bench 2, vendor-reported) or independently ranked 14th of 97 on the artificial analysis intelligence index. On a tight budget at scale, MiniMax M2.7 is the value pick.
DeepSeek V4 (DeepSeek) and MiniMax M2.7 (MiniMax) are two of the models people most often weigh against each other in 2026. DeepSeek V4 is china's open-weight price earthquake — near-frontier capability at roughly a twelfth of GPT-5.5's cost. MiniMax M2.7 is a cheap open-weight agentic coder with near-frontier terminal scores — held back by a non-commercial licence and non-standard benchmarks. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences
Price: MiniMax M2.7 is about 1.4× cheaper on input ($0.3/$1.2 per 1M tokens vs $0.435/$0.87 per 1M tokens) — modest, but it adds up at steady volume.
Context window: DeepSeek V4 holds 4.9× more — 1M (~1,500 pages) vs 205K (~307 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
Recency: DeepSeek V4 is the newer model by about 37 days (released April 24, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
DeepSeek V4
MiniMax M2.7
Provider
DeepSeek (China)
MiniMax (China)
Released
April 24, 2026
March 18, 2026
Context window
1M (~1,500 pages)
205K (~307 pages)
Price (in/out)
$0.435/$0.87 per 1M tokens
$0.3/$1.2 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, code
text, 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 — China's open-weight price earthquake — near-frontier capability at roughly a twelfth of GPT-5.5's cost — and it carries the larger 1M context.
Open MIT-licensed weights you can self-host: DeepSeek V4 — MiniMax M2.7 is comparatively weak here — open weights but a NON-COMMERCIAL licence — commercial use requires prior written authorisation from MiniMax, and at least one major tracker still mislabels it as MIT
No long-context surcharge: DeepSeek V4 — Its 1M window holds about 4.9× more than MiniMax M2.7's 205K in a single prompt.
Agentic and terminal coding well above its price tier (57.0 on Terminal-Bench 2, vendor-reported): MiniMax M2.7 — At $0.3/$1.2 per 1M tokens it undercuts DeepSeek V4 ($0.435/$0.87 per 1M tokens), and that gap compounds at volume.
Independently ranked 14th of 97 on the Artificial Analysis Intelligence Index: MiniMax M2.7 — A cheap open-weight agentic coder with near-frontier terminal scores — held back by a non-commercial licence and non-standard benchmarks — and it runs cheaper at $0.3/$1.2 per 1M tokens.
Sparse mixture-of-experts — roughly 230B total but only ~10B active, so it runs on local hardware: MiniMax M2.7 — MiniMax M2.7 lists sparse mixture-of-experts — roughly 230B total but only ~10B active, so it runs on local hardware among its strengths; DeepSeek V4 does not.
Lowest cost at scale: MiniMax M2.7 — At $0.3/$1.2 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input: DeepSeek V4 — Its 1M window is about 4.9× larger than MiniMax M2.7's 205K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: MiniMax M2.7 — At $0.3/$1.2 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: DeepSeek V4 — Larger 1M window fits more in one prompt.
Anyone whose priority is near-frontier coding at ~1/12 the cost: DeepSeek V4 — It is specifically built for that.
Anyone whose priority is agentic and terminal coding well above its price tier (57.0 on terminal-bench 2, vendor-reported): MiniMax M2.7 — That is its strongest area.
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.
MiniMax M2.7: where it fits
A cheap open-weight agentic coder with near-frontier terminal scores — held back by a non-commercial licence and non-standard benchmarks. Released March 18, 2026 by MiniMax, it is built for agentic and terminal coding well above its price tier (57.0 on Terminal-Bench 2, vendor-reported), independently ranked 14th of 97 on the Artificial Analysis Intelligence Index, sparse mixture-of-experts — roughly 230B total but only ~10B active, so it runs on local hardware, and served by five separate hosts at uniform pricing, so there is no provider lock-in.
Its trade-offs: open weights but a NON-COMMERCIAL licence — commercial use requires prior written authorisation from MiniMax, and at least one major tracker still mislabels it as MIT, reports SWE-Bench Pro instead of the standard Verified set, which blocks like-for-like comparison, and already superseded internally by M3, and its 205K context is small against 1M-class rivals. At $0.3 in / $1.2 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
DeepSeek V4 and MiniMax M2.7 overlap enough that the right pick depends on your specific job. MiniMax M2.7 costs less per token; DeepSeek V4 holds the larger context; and each leads in its own area — DeepSeek V4 for near-frontier coding at ~1/12 the cost, MiniMax M2.7 for agentic and terminal coding well above its price tier (57.0 on terminal-bench 2, vendor-reported). Rather than crowning one, run the same hard task through both once and let the results decide.
Frequently asked questions
Is DeepSeek V4 or MiniMax M2.7 better for coding?
Public SWE-Bench figures are not available for MiniMax M2.7, 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 MiniMax M2.7 leans toward agentic and terminal coding well above its price tier (57.0 on terminal-bench 2, vendor-reported), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, DeepSeek V4 or MiniMax M2.7?
MiniMax M2.7 is cheaper — $0.435/$0.87 per 1M tokens vs $0.3/$1.2 per 1M tokens, roughly 1.4× apart on input.
Which has the bigger context window?
DeepSeek V4 — 1M vs 205K, about 4.9× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both DeepSeek V4 and MiniMax M2.7 together?
Yes — a multi-model platform like LumiChats gives you DeepSeek V4, MiniMax M2.7 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 MiniMax M2.7?
DeepSeek V4 — released April 24, 2026, about 37 days after MiniMax M2.7.
DeepSeek V4 vs MiniMax M2.7
DeepSeek · China | MiniMax · China · 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 MiniMax M2.7 for agentic and terminal coding well above its price tier (57.0 on terminal-bench 2, vendor-reported) or independently ranked 14th of 97 on the artificial analysis intelligence index. On a tight budget at scale, MiniMax M2.7 is the value pick.
DeepSeek V4 (DeepSeek) and MiniMax M2.7 (MiniMax) are two of the models people most often weigh against each other in 2026. DeepSeek V4 is china's open-weight price earthquake — near-frontier capability at roughly a twelfth of GPT-5.5's cost. MiniMax M2.7 is a cheap open-weight agentic coder with near-frontier terminal scores — held back by a non-commercial licence and non-standard benchmarks. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
▸Price: MiniMax M2.7 is about 1.4× cheaper on input ($0.3/$1.2 per 1M tokens vs $0.435/$0.87 per 1M tokens) — modest, but it adds up at steady volume.
▸Context window: DeepSeek V4 holds 4.9× more — 1M (~1,500 pages) vs 205K (~307 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
▸Recency: DeepSeek V4 is the newer model by about 37 days (released April 24, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
DeepSeek V4
MiniMax M2.7
Provider
DeepSeek (China)
MiniMax (China)
Released
April 24, 2026
March 18, 2026
Context window
1M (~1,500 pages)
205K (~307 pages)
Price (in/out)
$0.435/$0.87 per 1M tokens
$0.3/$1.2 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, code
text, 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
China's open-weight price earthquake — near-frontier capability at roughly a twelfth of GPT-5.5's cost — and it carries the larger 1M context.
Open MIT-licensed weights you can self-host
DeepSeek V4
MiniMax M2.7 is comparatively weak here — open weights but a NON-COMMERCIAL licence — commercial use requires prior written authorisation from MiniMax, and at least one major tracker still mislabels it as MIT
No long-context surcharge
DeepSeek V4
Its 1M window holds about 4.9× more than MiniMax M2.7's 205K in a single prompt.
Agentic and terminal coding well above its price tier (57.0 on Terminal-Bench 2, vendor-reported)
MiniMax M2.7
At $0.3/$1.2 per 1M tokens it undercuts DeepSeek V4 ($0.435/$0.87 per 1M tokens), and that gap compounds at volume.
Independently ranked 14th of 97 on the Artificial Analysis Intelligence Index
MiniMax M2.7
A cheap open-weight agentic coder with near-frontier terminal scores — held back by a non-commercial licence and non-standard benchmarks — and it runs cheaper at $0.3/$1.2 per 1M tokens.
Sparse mixture-of-experts — roughly 230B total but only ~10B active, so it runs on local hardware
MiniMax M2.7
MiniMax M2.7 lists sparse mixture-of-experts — roughly 230B total but only ~10B active, so it runs on local hardware among its strengths; DeepSeek V4 does not.
Lowest cost at scale
MiniMax M2.7
At $0.3/$1.2 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
DeepSeek V4
Its 1M window is about 4.9× larger than MiniMax M2.7's 205K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ MiniMax M2.7
At $0.3/$1.2 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
→ DeepSeek V4
Larger 1M window fits more in one prompt.
Anyone whose priority is near-frontier coding at ~1/12 the cost
→ DeepSeek V4
It is specifically built for that.
Anyone whose priority is agentic and terminal coding well above its price tier (57.0 on terminal-bench 2, vendor-reported)
→ MiniMax M2.7
That is its strongest area.
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.
MiniMax M2.7: where it fits
A cheap open-weight agentic coder with near-frontier terminal scores — held back by a non-commercial licence and non-standard benchmarks. Released March 18, 2026 by MiniMax, it is built for agentic and terminal coding well above its price tier (57.0 on Terminal-Bench 2, vendor-reported), independently ranked 14th of 97 on the Artificial Analysis Intelligence Index, sparse mixture-of-experts — roughly 230B total but only ~10B active, so it runs on local hardware, and served by five separate hosts at uniform pricing, so there is no provider lock-in.
Its trade-offs: open weights but a NON-COMMERCIAL licence — commercial use requires prior written authorisation from MiniMax, and at least one major tracker still mislabels it as MIT, reports SWE-Bench Pro instead of the standard Verified set, which blocks like-for-like comparison, and already superseded internally by M3, and its 205K context is small against 1M-class rivals. At $0.3 in / $1.2 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
DeepSeek V4 and MiniMax M2.7 overlap enough that the right pick depends on your specific job. MiniMax M2.7 costs less per token; DeepSeek V4 holds the larger context; and each leads in its own area — DeepSeek V4 for near-frontier coding at ~1/12 the cost, MiniMax M2.7 for agentic and terminal coding well above its price tier (57.0 on terminal-bench 2, vendor-reported). Rather than crowning one, run the same hard task through both once and let the results decide.
Want both DeepSeek V4 and MiniMax M2.7 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 MiniMax M2.7, 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 MiniMax M2.7 leans toward agentic and terminal coding well above its price tier (57.0 on terminal-bench 2, vendor-reported), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, DeepSeek V4 or MiniMax M2.7?
MiniMax M2.7 is cheaper — $0.435/$0.87 per 1M tokens vs $0.3/$1.2 per 1M tokens, roughly 1.4× apart on input.
Which has the bigger context window?
DeepSeek V4 — 1M vs 205K, about 4.9× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both DeepSeek V4 and MiniMax M2.7 together?
Yes — a multi-model platform like LumiChats gives you DeepSeek V4, MiniMax M2.7 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 MiniMax M2.7?
DeepSeek V4 — released April 24, 2026, about 37 days after MiniMax M2.7.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.