AI Battle > Rankings > SciCode: Cost per Task

SciCode: Cost per Task Ranking — eval scicode (2026)

gpt-oss-120b (high) by OpenAI leads the SciCode: Cost per Task ranking with a score of 0.00. The ranking covers 20 evaluated eval scicode from a public dataset that AI Battle re-checks daily.

Last updated: . Source: public benchmark datasets and provider pricing, aggregated daily; 20 entries shown.

gpt-oss-120b (high)0.00Muse Glimmer (high)0.00GPT-5.6 Luna (max)0.00Gemini 3.7 Flash (medium)0.00Nemotron 3 Ultra 550B A55B (Reasoning)0.00DeepSeek V4.1 Flash (Reasoning, Max Effort)0.00Gemini 3.5 Flash-Lite0.00GLM-5.3-Flash0.00MiniMax-M30.01Grok 4.6 (high)0.00Muse Spark 1.1 (xhigh)0.00Muse Spark 1.3 (xhigh)0.00Muse Spark 1.3 (max)0.00DeepSeek V4 Pro 0813 (Reasoning, Max Effort)0.00Inkling (xhigh)0.00Kimi K3 (max)0.01Qwen3.8 27B (xhigh)0.00Gemini 3.8 Flash (high)0.00GPT-5.6 Sol (max)0.01Mistral Medium 3.50.00
Every entry in the dataset, scaled from the smallest to the largest published value.

All 20 entries in this dataset

#EntryCreatorValueΔ vs #1
1gpt-oss-120b (high)OpenAI0.000.0%
2Muse Glimmer (high)Meta0.0048.3%
3GPT-5.6 Luna (max)OpenAI0.0015.9%
4Gemini 3.7 Flash (medium)Google0.00262.8%
5Nemotron 3 Ultra 550B A55B (Reasoning)NVIDIA0.00237.1%
6DeepSeek V4.1 Flash (Reasoning, Max Effort)DeepSeek0.0036.5%
7Gemini 3.5 Flash-LiteGoogle0.0051.9%
8GLM-5.3-FlashZ AI0.00-3.6%
9MiniMax-M3MiniMax0.011202.7%
10Grok 4.6 (high)SpaceXAI0.00840.8%
11Muse Spark 1.1 (xhigh)Meta0.00652.0%
12Muse Spark 1.3 (xhigh)Meta0.00615.9%
13Muse Spark 1.3 (max)Meta0.00616.5%
14DeepSeek V4 Pro 0813 (Reasoning, Max Effort)DeepSeek0.00514.2%
15Inkling (xhigh)Thinking Machines0.00368.1%
16Kimi K3 (max)Kimi0.011425.5%
17Qwen3.8 27B (xhigh)Alibaba0.00305.7%
18Gemini 3.8 Flash (high)Google0.00288.7%
19GPT-5.6 Sol (max)OpenAI0.011852.2%
20Mistral Medium 3.5Mistral0.00466.9%

How the values are distributed

Across the 20 numeric entries in this window the median is 0.00 and the mean is 0.00, so the typical entry sits 0.00 above the leader. The window spans 0.00 to 0.01.

65510111
8 equal buckets between the smallest (0.00) and largest (0.01) value; numbers under bars are entry counts.

10 of 20 entries are at or above the median, and the top three hold 41% of the combined value — read it against the metric below, since a higher number is not "better" for every dataset.

Creators in this ranking

12 creators appear in this window; the three most-represented hold 50% of the entries.

CreatorEntriesHighest valueTop entry
Meta40.00Muse Spark 1.1 (xhigh)
OpenAI30.01GPT-5.6 Sol (max)
Google30.00Gemini 3.8 Flash (high)
DeepSeek20.00DeepSeek V4 Pro 0813 (Reasoning, Max Effort)
Kimi10.01Kimi K3 (max)
MiniMax10.01MiniMax-M3
SpaceXAI10.00Grok 4.6 (high)
Mistral10.00Mistral Medium 3.5
Thinking Machines10.00Inkling (xhigh)
Alibaba10.00Qwen3.8 27B (xhigh)
NVIDIA10.00Nemotron 3 Ultra 550B A55B (Reasoning)
Z AI10.00GLM-5.3-Flash

Where these models appear in other rankings

The same models are measured across multiple independent datasets. Aggregating the 20 entries above against every other AI Battle dataset gives this cross-section, computed by AI Battle and published nowhere upstream:

ModelDatasetsBest placements elsewhere
gpt-oss-120b (high)39#1/20 in Cost to Run Artificial Analysis Intelligence Index, #1/20 in Cost to Run Artificial Analysis Intelligence Index, #1/20 in Humanity's Last Exam: Cost per Task
Muse Glimmer (high)43#1/20 in Output Tokens per Intelligence Index Task, #1/20 in Cost per Intelligence Index Task, #1/20 in Cost per Intelligence Index Task
GPT-5.6 Luna (max)58#1/11 in Cost per Task, #1/11 in Cost per Task, #3/20 in Pricing: Cache Hit, Input, and Output
Gemini 3.7 Flash (medium)4#1/20 in SciCode: Time per Task, #2/20 in SciCode: Output Tokens per Task, #4/20 in SciCode: Score
Nemotron 3 Ultra 550B A55B (Reasoning)46#1/12 in Artificial Analysis Openness Index: Score, #1/12 in Artificial Analysis Openness Index: Components, #2/20 in 𝜏³-Banking: Time per Task
DeepSeek V4.1 Flash (Reasoning, Max Effort)56#3/20 in End-to-End Response Time, #3/20 in Latency: Time To First Answer Token, #2/11 in Cost per Task
Gemini 3.5 Flash-Lite44#1/20 in End-to-End Response Time, #1/20 in Output Speed, #1/20 in Time per Intelligence Index Task
GLM-5.3-Flash54#1/20 in Pricing: Cache Hit, Input, and Output, #1/20 in Pricing: Cache Hit, Input, and Output, #1/20 in AA-Omniscience Index: Cost Breakdown
MiniMax-M357#1/20 in AA-Omniscience Hallucination Rate, #1/20 in 𝜏³-Banking: Output Tokens per Task, #4/20 in Pricing: Cache Hit, Input, and Output
Grok 4.6 (high)61#2/20 in 𝜏³-Banking: Score, #5/20 in AA-Briefcase Elo, #5/20 in AA-Omniscience Index
Muse Spark 1.1 (xhigh)3#9/20 in SciCode: Score, #15/20 in SciCode: Output Tokens per Task
Muse Spark 1.3 (xhigh)12#3/20 in 𝜏³-Banking: Time per Task, #5/20 in SciCode: Score, #7/20 in GDPval-AA v2 Leaderboard
Muse Spark 1.3 (max)61#3/20 in AA-Briefcase Elo, #3/20 in Output Speed, #3/20 in GDPval-AA v2 Leaderboard
DeepSeek V4 Pro 0813 (Reasoning, Max Effort)59#3/14 in Model Size: Total and Active Parameters, #3/12 in Artificial Analysis Openness Index: Score, #3/11 in Cost per Task
Inkling (xhigh)52#3/20 in Context Window, #3/20 in 𝜏³-Banking: Output Tokens per Task, #5/20 in AA-Briefcase Output Tokens per Task
Kimi K3 (max)60#1/20 in Context Window, #1/20 in AA-LCR v1.1: Score, #1/14 in Model Size: Total and Active Parameters
Qwen3.8 27B (xhigh)43#6/20 in AA-Omniscience Hallucination Rate, #6/20 in 𝜏³-Banking: Score, #8/20 in AA-LCR v1.1: Cost per Task
Gemini 3.8 Flash (high)60#1/11 in Speed, #1/11 in Speed, #2/20 in Output Speed
GPT-5.6 Sol (max)56#3/20 in SciCode: Output Tokens per Task, #4/20 in 𝜏³-Banking: Output Tokens per Task, #5/20 in AA-LCR v1.1: Output Tokens per Task
Mistral Medium 3.541#2/20 in GDPval-AA v2: Output Tokens per Task, #3/20 in Output Tokens per Intelligence Index Task, #3/20 in Output Tokens per Intelligence Index Task

Metric reference

This ranking carries the metrics answer, cacheHit, cacheWrite, input, reasoning from the SciCode: Cost per Task dataset in the tab::eval-scicode family. Units and the direction of "better" are not declared by the source dataset, so AI Battle does not invent them: values are shown exactly as published, and the ordering is the source dataset's own.

How this ranking is built

Rebuilt on from the public dataset SciCode: Cost per Task (family tab::eval-scicode). The source lists 20 entries and all 20 are shown here. AI Battle requests the dataset's rows, keeps the ordering the source publishes, and computes only the statistics on this page: median, mean, spread, the #1–#2 gap, the creator breakdown and the raw-data file. Nothing on this page is generated text about the entries — the numbers come from the source.

Refresh cadence: every deploy re-pulls the dataset, so this page tracks the source's own update cycle. Corrections: see the methodology page.

Limitations

Raw data

Machine-readable copy of this table, with the statistics below and the source provenance: /data/rankings/eval-scicode-scicode-cost-per-task.json. Free to reuse with attribution to AI Battle and the source dataset.

FAQ — SciCode: Cost per Task

What is the best model for SciCode: Cost per Task in 2026?

gpt-oss-120b (high) by OpenAI currently leads the SciCode: Cost per Task ranking with a score of 0.00, the highest value in this dataset across eval scicode. AI Battle aggregates the dataset from its public source and re-checks it daily.

How often is the SciCode: Cost per Task ranking updated?

The SciCode: Cost per Task ranking is rebuilt daily from the upstream public dataset. Scores are the source dataset's own published values, so positions track whatever that source last released — each ranking page names the dataset it comes from.

Which models rank in the top 3 for SciCode: Cost per Task?

The top 3 are: 1. gpt-oss-120b (high) (0.00), 2. Muse Glimmer (high) (0.00), 3. GPT-5.6 Luna (max) (0.00).

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