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ALLaM 1 13B Instruct vs autofixer-01

vs
autofixer-01

Vercel

26#420
Signal-by-Signal Comparison
SignalALLaM 1 13B InstructDeltaautofixer-01
Capabilities
17
--
17
Pricing
98
-2
100
Context window size
57
+57
0
Recency
14
-55
70
Output Capacity
58
+38
20
Overall Result
2 wins
of 5
2 wins
It's a tie - both models win 2 signals each

Score History

Score History (26 data points)
ALLaM 1 13B Instructautofixer-01
ALLaM 1 13B Instruct

32.4

current score

Leader

ALLaM 1 13B Instruct

right now

autofixer-01

26.2

current score

LMMarketCap.com
Interactive Price Comparison
100Kcalls/month
1,000tokens (~1,333 chars)
500tokens (~667 chars)

ALLaM 1 13B Instruct

HUMAIN

Per request$0.002700
Daily$9.00
Monthly$270.00
Annual$3240.00

autofixer-01

Vercel

Best Value
Per request$0.000000
Daily$0.00
Monthly$0.00
Annual$0.00

autofixer-01 saves you $270.00/month

That's $3240.00/year compared to ALLaM 1 13B Instruct at your current usage level of 100K calls/month.

100% cheaper
Choose autofixer-01 for cost optimization

ALLaM 1 13B Instruct pricing:
Input:$1.80/M tokens
Output:$1.80/M tokens
autofixer-01 pricing:
Input:$0.00/M tokens
Output:$0.00/M tokens
Winner
ALLaM 1 13B Instruct

HUMAIN

32

Composite Score

autofixer-01

Vercel

26

Composite Score

Signal-by-Signal Comparison
MetricALLaM 1 13B Instructautofixer-01Winner
Overall Score
32
26
ALLaM 1 13B Instruct
Rank#418#420
ALLaM 1 13B Instruct
Quality Rank#418#420
ALLaM 1 13B Instruct
Adoption Rank#418#420
ALLaM 1 13B Instruct
Parameters13B----
Context Window4K----
Pricing$1.80/$1.80/MFree--
Signal Scores
Capabilities
17
17
ALLaM 1 13B Instruct
Pricing
98
100
autofixer-01
Context window size
57
0
ALLaM 1 13B Instruct
Recency
14
70
autofixer-01
Output Capacity
58
20
ALLaM 1 13B Instruct
Benchmark Interpretation

Our score (0-100) is driven by benchmark performance (90%) from Arena Elo ratings, MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations. Capabilities and context window serve as tiebreakers (10%). Learn more about our methodology.

ALLaM 1 13B InstructEntry Level

Scores 32/100 (rank #418), placing it in the top -44% of all 290 models tracked.

Raw Quality0/100
Cost Efficiency0/100
Speed0/100
autofixer-01Limited

Scores 26/100 (rank #420), placing it in the top -44% of all 290 models tracked.

Raw Quality0/100
Cost Efficiency0/100
Speed0/100

ALLaM 1 13B Instruct has a 6-point advantage, which typically translates to noticeably better performance on complex reasoning, code generation, and multi-step tasks.

When to Use Each Model

Choose ALLaM 1 13B Instruct when you need:

  • Budget-friendly applications with moderate quality requirements

Choose autofixer-01 when you need:

  • High-volume production workloads where API costs must be minimized
Cost-Performance Analysis
ALLaM 1 13B Instruct
Input cost$1.80/M tokens
Output cost$1.80/M tokens
Cost per quality point$0.111
Est. monthly (1M tokens/day)$54.00
autofixer-01
Input cost$0.00/M tokens
Output cost$0.00/M tokens
Cost per quality point$0.000
Est. monthly (1M tokens/day)$0.00

Both models are priced similarly, so the decision comes down to quality and features rather than cost.

Latency & Speed
ALLaM 1 13B InstructFaster
Speed score0/100
autofixer-01
Speed score0/100

Both models have comparable response speeds. For most applications, the latency difference is negligible.

When latency matters most: Interactive chatbots, IDE code completion, real-time translation, and user-facing applications where response time directly impacts experience. For batch processing, background summarization, or offline analysis, latency is less critical.

Example Use Cases

Code generation & review

Based on overall model capabilities and architecture for coding tasks like generating functions, debugging, and refactoring

ALLaM 1 13B Instruct

Customer support chatbot

Suitable for user-facing chat with competitive response times. autofixer-01 also offers lower per-token costs for high-volume support

ALLaM 1 13B Instruct

Long document analysis

Larger context window (4K tokens) can process longer documents, contracts, and research papers in a single pass

ALLaM 1 13B Instruct

Batch data extraction

Lower output pricing ($0.00/M) reduces costs when processing thousands of records daily

autofixer-01

Creative writing & content

Higher overall composite score (32/100) correlates with better nuance, coherence, and style in long-form content

ALLaM 1 13B Instruct
Which Should You Choose?
Our recommendation:
ALLaM 1 13B Instruct

ALLaM 1 13B Instruct has a moderate advantage with a 6.199999999999999-point lead in composite score. It wins on more signal dimensions, but autofixer-01 has specific strengths that could make it the better choice for certain workflows.

by HUMAIN

  • Choose for Quality - Marginally better benchmark scores; both are excellent
  • Choose for Reliability - Higher uptime and faster response speeds
  • Choose for Prototyping - Stronger community support and better developer experience
  • Choose for Production - Wider enterprise adoption and proven at scale

by Vercel

  • Choose for Cost - 100% lower pricing; better value at scale
Capability Comparison
CapabilityALLaM 1 13B Instructautofixer-01
Vision (Image Input)
Function Calling
Streaming
JSON Mode
Reasoning
Web Search
Image Output
Monthly Cost Calculator
1,000tokens (600 in / 400 out)
100requests/day (3,000/month)

ALLaM 1 13B Instruct

HUMAIN

$5.40
estimated monthly cost

autofixer-01

Vercel

Best Value
$0.000000
estimated monthly cost

autofixer-01 saves you $5.40/month

That's 100% cheaper than ALLaM 1 13B Instruct at 1,000 tokens/request and 100 requests/day.

Assumes 60% input / 40% output token ratio per request. Actual costs may vary based on your usage pattern.

Parameters & Context
ParameterALLaM 1 13B Instructautofixer-01
Context Window4K--
Max Output Tokens4,096--
Open SourceNoNo
CreatedDec 1, 2024Oct 1, 2025
Last updated: 21m ago

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ALLaM 1 13B Instruct vs autofixer-01 (2026) | LM Market Cap