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Comparisons

Deepseek Coder 33B Instruct vs MiniMax M2.7 FP4

On provider list prices, MiniMax M2.7 FP4 costs $0.30 per million input tokens against $0.80 for Deepseek Coder 33B Instruct: 2.7x apart. Output is $1.20 against $0.80. On Allocate both bill at list plus the 7% transaction fee.

Deepseek Coder 33B InstructM MiniMax M2.7 FP4
LabDeepseekMiniMaxAI
AccessOpen weightsOpen weights
Context window16K tokens192K tokens
List price, input$0.8 / M tokens$0.3 / M tokens
List price, output$0.8 / M tokens$1.2 / M tokens
Cached inputn/a$0.06 / M tokens
LicenseCustom licenseNot listed
Fine-tunableYesYes

Specifications and provider list prices from the Allocate catalog, checked 2026-07-08. Billed price is list plus the 7% transaction fee.

What the numbers say

Take 1,000,000 requests a month at 1,200 input and 350 output tokens each. That workload costs $780 a month on MiniMax M2.7 FP4 and $1,240 on Deepseek Coder 33B Instruct at list: a gap of $460, or 1.6x.

MiniMax M2.7 FP4 reads 192K tokens per request against 16K for Deepseek Coder 33B Instruct, 12.0x the window. That decides which one can take whole documents without splitting them.

MiniMax M2.7 FP4$0.30$1.20
Deepseek Coder 33B Instruct$0.80$0.80
InputOutput

Choose Deepseek Coder 33B Instruct for

  • Training toward a model you own
Deepseek Coder 33B Instruct details

Choose MiniMax M2.7 FP4 for

  • The lower list price ($0.30 in / $1.20 out per M tokens)
  • The longer context window (192K vs 16K tokens)
  • Published cached-input pricing ($0.06 per M tokens)
MiniMax M2.7 FP4 details

Common questions

Which is cheaper, Deepseek Coder 33B Instruct or MiniMax M2.7 FP4?

MiniMax M2.7 FP4, on this workload shape. At list prices it is $0.30/$1.20 per million tokens in and out against $0.80/$0.80 for Deepseek Coder 33B Instruct. Billed on Allocate: $0.32/$1.28 against $0.86/$0.86, list plus 7%.

Which has the bigger context window?

MiniMax M2.7 FP4: 196,608 tokens (192K) against 16,384 (16K) for Deepseek Coder 33B Instruct.

Can I fine-tune Deepseek Coder 33B Instruct or MiniMax M2.7 FP4?

Both publish open weights (Deepseek Coder 33B Instruct: Custom license; MiniMax M2.7 FP4: Not listed), so both can be fine-tuned. On Allocate the trained weights stay inside your boundary and belong to you.

Related comparisons

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Run the numbers on your workload

LLM price comparisonAgent cost calculatorDeepseek Coder 33B InstructMiniMax M2.7 FP4

Or don’t choose. On Allocate a route name is the contract: point yours at one model today, swap to the other tomorrow, and compare them on your live traffic with per-token metering.

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