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MiniMax M2.1 vs ReMM SLERP 13B

ReMM SLERP 13B costs 1.8x less per output token than MiniMax M2.1 ($0.65 vs $1.20 per million). Updated October 23, 2026; no benchmark has tested both models yet.

MiniMax M2.1MiniMax
Coding
No data
Overall
No data
Output $/M
$1.20
U ReMM SLERP 13BUndi95
Coding
No data
Overall
No data
Output $/M
$0.65
vs $1.20 vs $0.65 per 1M output tokens. ReMM SLERP 13B is 1.8x cheaper.

MiniMax M2.1 or ReMM SLERP 13B: which to pick

Neither model has a coding score yet, so the two cannot be ranked on coding.

Pick MiniMax M2.1 for a larger context window (205K against 6K tokens).

No benchmark has tested both yet. MiniMax M2.1 has results on LiveCodeBench (Vals AI), SWE-bench Verified (Vals AI) and LiveCodeBench (Artificial Analysis run); ReMM SLERP 13B has none yet. Compare them on price and context instead.

Which one for your work

Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.

At a glance

Coding index
MiniMax M2.1 not benchmarked, ReMM SLERP 13B not benchmarked.
Widest category
None yet: no category has been tested on both models.
Widest single gap
None yet: no benchmark has tested both models.
Output price
MiniMax M2.1 $1.20 against ReMM SLERP 13B $0.65 per million output tokens, 1.8x apart.
Context window
MiniMax M2.1 takes 205K tokens, ReMM SLERP 13B 6K.

Benchmark by benchmark

Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.

CodingDirectional onlySix of these boards feed the Vibe Coding Index6 boards measured
Coding benchmarks for MiniMax M2.1 and ReMM SLERP 13B
BenchmarkMiniMax M2.1ReMM SLERP 13BLeader
LiveCodeBench (Vals AI)81.8%Not measuredOnly MiniMax M2.1 measured
SWE-bench Verified (Vals AI)74.8%Not measuredOnly MiniMax M2.1 measured
LiveCodeBench (Artificial Analysis run)81.0%Not measuredOnly MiniMax M2.1 measured
Terminal-Bench Hard (Artificial Analysis run)28.8%Not measuredOnly MiniMax M2.1 measured
Terminal-Bench36.6%Not measuredOnly MiniMax M2.1 measured
ALE-Bench623.8Not measuredOnly MiniMax M2.1 measured
Neither model has a result on the other 37 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
Intelligence benchmarks for MiniMax M2.1 and ReMM SLERP 13B
BenchmarkMiniMax M2.1ReMM SLERP 13BLeader
AA Intelligence Index20.9Not measuredOnly MiniMax M2.1 measured
Neither model has a result on the other 1 board here
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
Agentic work benchmarks for MiniMax M2.1 and ReMM SLERP 13B
BenchmarkMiniMax M2.1ReMM SLERP 13BLeader
τ²-Bench Telecom85.4%Not measuredOnly MiniMax M2.1 measured
Neither model has a result on the other 41 boards here
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
Reasoning benchmarks for MiniMax M2.1 and ReMM SLERP 13B
BenchmarkMiniMax M2.1ReMM SLERP 13BLeader
GPQA Diamond78.5%Not measuredOnly MiniMax M2.1 measured
GPQA Diamond (Artificial Analysis run)83.0%Not measuredOnly MiniMax M2.1 measured
Humanity's Last Exam (Artificial Analysis run)23.2%Not measuredOnly MiniMax M2.1 measured
Neither model has a result on the other 20 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index5 boards measured
Math benchmarks for MiniMax M2.1 and ReMM SLERP 13B
BenchmarkMiniMax M2.1ReMM SLERP 13BLeader
AIME77.9%Not measuredOnly MiniMax M2.1 measured
MATH 500 (Vals AI)89.0%Not measuredOnly MiniMax M2.1 measured
MGSM (Vals AI)87.8%Not measuredOnly MiniMax M2.1 measured
AA Math Index82.7Not measuredOnly MiniMax M2.1 measured
AIME 2025 (Artificial Analysis run)82.7%Not measuredOnly MiniMax M2.1 measured
Neither model has a result on the other 9 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index8 boards measured
Knowledge benchmarks for MiniMax M2.1 and ReMM SLERP 13B
BenchmarkMiniMax M2.1ReMM SLERP 13BLeader
MMLU Pro87.0%Not measuredOnly MiniMax M2.1 measured
LegalBench (Vals AI)75.5%Not measuredOnly MiniMax M2.1 measured
CaseLaw (Vals AI)55.8%Not measuredOnly MiniMax M2.1 measured
CorpFin (Vals AI)58.9%Not measuredOnly MiniMax M2.1 measured
TaxEval (Vals AI)66.3%Not measuredOnly MiniMax M2.1 measured
MedQA (Vals AI)91.2%Not measuredOnly MiniMax M2.1 measured
MedCode (Vals AI)34.1%Not measuredOnly MiniMax M2.1 measured
MMLU Pro (Artificial Analysis run)87.5%Not measuredOnly MiniMax M2.1 measured
Neither model has a result on the other 12 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards measured
Web design benchmarks for MiniMax M2.1 and ReMM SLERP 13B
BenchmarkMiniMax M2.1ReMM SLERP 13BLeader
Design Arena: websites1201Not measuredOnly MiniMax M2.1 measured
Design Arena: UI components1220Not measuredOnly MiniMax M2.1 measured
Design Arena: game dev1134Not measuredOnly MiniMax M2.1 measured
Design Arena: data viz1207Not measuredOnly MiniMax M2.1 measured
Design Arena: 3D1166Not measuredOnly MiniMax M2.1 measured
Design Arena: all code categories1190Not measuredOnly MiniMax M2.1 measured
Design Arena: SVG1131Not measuredOnly MiniMax M2.1 measured
Neither model has a result on the other 2 boards here
GeneralDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
General benchmarks for MiniMax M2.1 and ReMM SLERP 13B
BenchmarkMiniMax M2.1ReMM SLERP 13BLeader
MedScribe (Vals AI)80.8%Not measuredOnly MiniMax M2.1 measured
IFBench69.9%Not measuredOnly MiniMax M2.1 measured
Long context reasoning (AA-LCR)67.7%Not measuredOnly MiniMax M2.1 measured
Neither model has a result on the other 45 boards here

What each workload costs

Three fixed token mixes at each model's listed price, so per-token rates become a bill.

Chat turn

1K input + 500 output tokens

MiniMax M2.1$0.0009Fits in one request
ReMM SLERP 13B$0.0007Fits in one request

ReMM SLERP 13B costs less

Repository review

50K input + 3K output tokens

MiniMax M2.1$0.019Fits in one request
ReMM SLERP 13B$0.019Exceeds the context window

MiniMax M2.1 costs less

Agent loop

200K input + 10K output tokens

MiniMax M2.1$0.072Exceeds the context window
ReMM SLERP 13B$0.076Exceeds the context window

MiniMax M2.1 costs less

Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.

Specification differences

The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.

Specifications of MiniMax M2.1 and ReMM SLERP 13B
SpecificationMiniMax M2.1ReMM SLERP 13B
MakerMiniMaxUndi95
WeightsOpen weightsOpen weights
ReleasedDecember 23, 2025July 22, 2023
Context window205K6K
Input $/Mtok$0.30$0.35
Output $/Mtok$1.20$0.65
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it10
Cost per solved task$0.59Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is MiniMax M2.1 better than ReMM SLERP 13B for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick MiniMax M2.1 for a larger context window (205K against 6K tokens).

Which is cheaper, MiniMax M2.1 or ReMM SLERP 13B?

MiniMax M2.1 costs $0.30 per million input tokens and $1.20 per million output tokens; ReMM SLERP 13B costs $0.35 and $0.65. Cost per solved task is known for MiniMax M2.1 only.

Which has the bigger context window, MiniMax M2.1 or ReMM SLERP 13B?

MiniMax M2.1, with 205K tokens against 6K.

Has any benchmark tested both MiniMax M2.1 and ReMM SLERP 13B?

No benchmark has tested both yet. MiniMax M2.1 has results on LiveCodeBench (Vals AI), SWE-bench Verified (Vals AI) and LiveCodeBench (Artificial Analysis run); ReMM SLERP 13B has none yet. Compare them on price and context instead. Data as of October 23, 2026.

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