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Ember-1 vs MiniMax M2.5

Ember-1 leads MiniMax M2.5 on coding, 52.6 to 37.2 on the Vibe Coding Index, and MiniMax M2.5 costs 12.5x less per output token ($1.20 vs $15.00 per million). Updated October 22, 2026; 1 benchmarks have a result for both.

Ember-1Fireworks
Coding
52.6
Overall
No data
Output $/M
$15.00
1
MiniMax M2.5MiniMax
Coding
37.2
Overall
37.3
Output $/M
$1.20
0
vs boards won of 1 shared

Ember-1 or MiniMax M2.5: which to pick

Pick Ember-1 for coding: it scores 52.6 on the Vibe Coding Index against 37.2 for MiniMax M2.5, though on 2 benchmarks against 3.

Pick MiniMax M2.5 for output tokens 12.5x cheaper ($1.20 vs $15.00 per million).

Shared results
1
Ember-1 only
13
MiniMax M2.5 only
67
Like-for-like categories
1 of 9

Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.

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
Ember-1 52.6 from 2 benchmarks, MiniMax M2.5 37.2 from 3 benchmarks.
Widest category
Coding, 69.0 points apart on average over 1 shared benchmark.
Widest single gap
Vibe Code Bench (Vals AI): Ember-1 83.9% against MiniMax M2.5 14.8%, 69.0 points apart on a 0 to 100 scale.
Output price
Ember-1 $15.00 against MiniMax M2.5 $1.20 per million output tokens, 12.5x apart.
Context window
Ember-1 takes 1.05M tokens, MiniMax M2.5 205K.

Benchmark by benchmark

First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.

Boards won, where both have a result
CategoryEmber-1BarsMiniMax M2.5Ties
Coding10
All shared boards10
CodingLike-for-likeSix of these boards feed the Vibe Coding Index10
Coding benchmarks for Ember-1 and MiniMax M2.5
BenchmarkEmber-1MiniMax M2.5Leader
SWE-bench VerifiedNot measured75.8%Only MiniMax M2.5 measured
SWE-bench MultilingualNot measured68.3%Only MiniMax M2.5 measured
LMArena WebDevNot measured1386Only MiniMax M2.5 measured
LiveCodeBench (Vals AI)Not measured79.2%Only MiniMax M2.5 measured
SWE-bench Verified (Vals AI)Not measured74.2%Only MiniMax M2.5 measured
Terminal-Bench 4 (Vals AI)20.7%Not measuredOnly Ember-1 measured
Vibe Code Bench (Vals AI)83.9%14.8%Ember-1
Code migration (Vals AI)32.5%Not measuredOnly Ember-1 measured
IOI (Vals AI)46.3%Not measuredOnly Ember-1 measured
CyberBench (Vals AI)69.5%Not measuredOnly Ember-1 measured
Terminal-Bench Hard (Artificial Analysis run)Not measured34.8%Only MiniMax M2.5 measured
Terminal-BenchNot measured42.7%Only MiniMax M2.5 measured
ALE-BenchNot measured618.2Only MiniMax M2.5 measured
LMArena Text: codingNot measured1380Only MiniMax M2.5 measured
LMArena Text: software and ITNot measured1383Only MiniMax M2.5 measured
LMArena WebDev: ReactNot measured1374Only MiniMax M2.5 measured
LMArena WebDev: HTMLNot measured1414Only MiniMax M2.5 measured
Neither model has a result on the other 22 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Intelligence benchmarks for Ember-1 and MiniMax M2.5
BenchmarkEmber-1MiniMax M2.5Leader
AA Intelligence IndexNot measured22.8Only MiniMax M2.5 measured
Epoch Capabilities IndexNot measured146.6Only MiniMax M2.5 measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
Agentic work benchmarks for Ember-1 and MiniMax M2.5
BenchmarkEmber-1MiniMax M2.5Leader
Finance Agent (Vals AI)51.8%Not measuredOnly Ember-1 measured
Tax Agent Bench (Vals AI)31.1%Not measuredOnly Ember-1 measured
Legal Research Bench (Vals AI)44.7%Not measuredOnly Ember-1 measured
Excel Modeling Benchmark (Vals AI)63.4%Not measuredOnly Ember-1 measured
BioMysteryBench (Vals AI)67.0%Not measuredOnly Ember-1 measured
Terminal-Bench-Science (Vals AI)5.7%Not measuredOnly Ember-1 measured
Vals Science Index31.8%Not measuredOnly Ember-1 measured
τ²-Bench TelecomNot measured95.3%Only MiniMax M2.5 measured
Vending-Bench 2Not measured-$23Only MiniMax M2.5 measured
Neither model has a result on the other 32 boards here
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index10 boards, none shared
Reasoning benchmarks for Ember-1 and MiniMax M2.5
BenchmarkEmber-1MiniMax M2.5Leader
GPQA DiamondNot measured82.1%Only MiniMax M2.5 measured
MysteryMechanism (Vals AI)22.5%Not measuredOnly Ember-1 measured
GPQA Diamond (Artificial Analysis run)Not measured84.8%Only MiniMax M2.5 measured
Humanity's Last Exam (Artificial Analysis run)Not measured20.5%Only MiniMax M2.5 measured
ARC-AGINot measured63.7%Only MiniMax M2.5 measured
ARC-AGI-2Not measured4.9%Only MiniMax M2.5 measured
LMArena Text: hard promptsNot measured1372Only MiniMax M2.5 measured
LMArena Text: expertNot measured1378Only MiniMax M2.5 measured
LMArena Text: hard prompts in EnglishNot measured1384Only MiniMax M2.5 measured
Kagi LLM BenchmarkNot measured55.2%Only MiniMax M2.5 measured
Neither model has a result on the other 12 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
Math benchmarks for Ember-1 and MiniMax M2.5
BenchmarkEmber-1MiniMax M2.5Leader
AIMENot measured88.8%Only MiniMax M2.5 measured
ProofBenchNot measured4.0%Only MiniMax M2.5 measured
LMArena Text: mathNot measured1378Only MiniMax M2.5 measured
LMArena Text: mathematical workNot measured1378Only MiniMax M2.5 measured
Neither model has a result on the other 9 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index10 boards, none shared
Knowledge benchmarks for Ember-1 and MiniMax M2.5
BenchmarkEmber-1MiniMax M2.5Leader
MMLU ProNot measured80.1%Only MiniMax M2.5 measured
LegalBench (Vals AI)Not measured80.0%Only MiniMax M2.5 measured
CaseLaw (Vals AI)Not measured53.5%Only MiniMax M2.5 measured
CorpFin (Vals AI)Not measured59.6%Only MiniMax M2.5 measured
TaxEval (Vals AI)Not measured68.2%Only MiniMax M2.5 measured
MedQA (Vals AI)Not measured92.5%Only MiniMax M2.5 measured
LMArena Text: scienceNot measured1369Only MiniMax M2.5 measured
LMArena Text: medicine and healthcareNot measured1357Only MiniMax M2.5 measured
LMArena Text: legal and governmentNot measured1366Only MiniMax M2.5 measured
LMArena Text: business and financeNot measured1356Only MiniMax M2.5 measured
Neither model has a result on the other 8 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
Web design benchmarks for Ember-1 and MiniMax M2.5
BenchmarkEmber-1MiniMax M2.5Leader
Design Arena: websitesNot measured1222Only MiniMax M2.5 measured
Design Arena: UI componentsNot measured1170Only MiniMax M2.5 measured
Design Arena: game devNot measured1176Only MiniMax M2.5 measured
Design Arena: data vizNot measured1172Only MiniMax M2.5 measured
Design Arena: 3DNot measured1170Only MiniMax M2.5 measured
Design Arena: all code categoriesNot measured1207Only MiniMax M2.5 measured
Design Arena: SVGNot measured1150Only MiniMax M2.5 measured
Neither model has a result on the other 2 boards here
GeneralDirectional onlyPublic boards, shown as published, kept out of the index22 boards, none shared
General benchmarks for Ember-1 and MiniMax M2.5
BenchmarkEmber-1MiniMax M2.5Leader
Public Benefits Bench (Vals AI)66.2%Not measuredOnly Ember-1 measured
IFBenchNot measured71.6%Only MiniMax M2.5 measured
Long context reasoning (AA-LCR)Not measured73.3%Only MiniMax M2.5 measured
CL-benchNot measured11.4%Only MiniMax M2.5 measured
CL-bench LifeNot measured6.3%Only MiniMax M2.5 measured
LMArena TextNot measured1359Only MiniMax M2.5 measured
LMArena Text: instruction followingNot measured1353Only MiniMax M2.5 measured
LMArena Text: creative writingNot measured1331Only MiniMax M2.5 measured
LMArena Text: EnglishNot measured1380Only MiniMax M2.5 measured
LMArena Text: non-EnglishNot measured1338Only MiniMax M2.5 measured
LMArena Text: ChineseNot measured1393Only MiniMax M2.5 measured
LMArena Text: GermanNot measured1361Only MiniMax M2.5 measured
LMArena Text: JapaneseNot measured1171Only MiniMax M2.5 measured
LMArena Text: KoreanNot measured1233Only MiniMax M2.5 measured
LMArena Text: FrenchNot measured1363Only MiniMax M2.5 measured
LMArena Text: SpanishNot measured1353Only MiniMax M2.5 measured
LMArena Text: RussianNot measured1359Only MiniMax M2.5 measured
LMArena Text: PolishNot measured1334Only MiniMax M2.5 measured
LMArena Text: multi-turnNot measured1364Only MiniMax M2.5 measured
LMArena Text: longer queriesNot measured1366Only MiniMax M2.5 measured
LMArena Text: writing and languageNot measured1345Only MiniMax M2.5 measured
LMArena Text: entertainment and mediaNot measured1329Only MiniMax M2.5 measured
Neither model has a result on the other 24 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Ember-1 and MiniMax M2.5
BenchmarkEmber-1MiniMax M2.5Leader
Neither model has a result on 5 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

Ember-1$0.011Fits in one request
MiniMax M2.5$0.0009Fits in one request

MiniMax M2.5 costs less

Repository review

50K input + 3K output tokens

Ember-1$0.195Fits in one request
MiniMax M2.5$0.019Fits in one request

MiniMax M2.5 costs less

Agent loop

200K input + 10K output tokens

Ember-1$0.750Fits in one request
MiniMax M2.5$0.072Exceeds the context window

MiniMax M2.5 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 Ember-1 and MiniMax M2.5
SpecificationFireworks Ember-1MiniMax M2.5
MakerFireworksMiniMax
WeightsNo public weights listedOpen weights
ReleasedSeptember 24, 2026February 12, 2026
Context window1.05M205K
Input $/Mtok$3.00$0.30
Output $/Mtok$15.00$1.20
Coding index52.637.2
Independent measurements behind it23
Cost per solved taskNot computable$0.62
SourceOpenRouter listingOpenRouter listing

Questions

Is Ember-1 better than MiniMax M2.5 for coding?

Pick Ember-1 for coding: it scores 52.6 on the Vibe Coding Index against 37.2 for MiniMax M2.5, though on 2 benchmarks against 3. Pick MiniMax M2.5 for output tokens 12.5x cheaper ($1.20 vs $15.00 per million).

Which is cheaper, Ember-1 or MiniMax M2.5?

Ember-1 costs $3.00 per million input tokens and $15.00 per million output tokens; MiniMax M2.5 costs $0.30 and $1.20. Cost per solved task is known for MiniMax M2.5 only.

Which has the bigger context window, Ember-1 or MiniMax M2.5?

Ember-1, with 1.05M tokens against 205K.

How many benchmarks is the Ember-1 vs MiniMax M2.5 comparison based on?

1 benchmarks have a result for both models as of October 22, 2026. Ember-1's coding index rests on 2 independent benchmarks and MiniMax M2.5's on 3. Where only one model has a result, the page says so instead of naming a winner.

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<iframe src="https://llmbenchmark.ai/embed/compare/fireworks-ember-1-vs-minimax-minimax-m2-5" title="Ember-1 vs MiniMax M2.5, LLMBenchmark.ai" width="100%" height="360" style="border:0;max-width:100%" loading="lazy"></iframe>
<p style="font:13px/1.4 sans-serif;margin:6px 0 0">Source: <a href="https://llmbenchmark.ai/compare/fireworks-ember-1-vs-minimax-minimax-m2-5">LLMBenchmark.ai, Ember-1 vs MiniMax M2.5</a></p>