# 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.

## Specifications

| | Deepseek Coder 33B Instruct | MiniMax M2.7 FP4 |
| --- | --- | --- |
| Lab | Deepseek | MiniMaxAI |
| Access | Open weights | Open weights |
| Context window | 16K tokens | 192K tokens |
| List price, input | $0.80 / M tokens | $0.30 / M tokens |
| List price, output | $0.80 / M tokens | $1.20 / M tokens |
| Cached input | n/a | $0.06 / M tokens |
| License | Custom license | Not listed |
| Fine-tunable | Yes | Yes |

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.

## Choose Deepseek Coder 33B Instruct for

- Training toward a model you own

## 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)

## 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.

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[HTML page](https://allocate.network/compare/deepseek-deepseek-coder-33b-instruct-vs-minimaxai-minimax-m2-7) · [Deepseek Coder 33B Instruct](https://allocate.network/models/deepseek-deepseek-coder-33b-instruct.md) · [MiniMax M2.7 FP4](https://allocate.network/models/minimaxai-minimax-m2-7.md) · [Machine-readable catalog](https://allocate.network/catalog.json)