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InternLM Intern-Decision Qwen3.5-0.8B

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InternLM Intern-Decision Qwen3.5-0.8B is an open-weights decision model from Shanghai AI Laboratory (InternLM). Its published size is 0.87B parameters. Licence: apache-2.0.

Catalogue identity notes

Exact Decision Index tested engine intern-decision-0.8b; reported model InternLM Intern-Decision Qwen3.5-0.8B. Type: full fine-tune; technique: autoregressive. Implementation: https://github.com/internlm/Intern-Decision. Comparison entry; no current run command, API price or speed inferred from the benchmark. Current repository metadata checked separately; an unpinned alias is not evidence that today’s weights reproduce this historical run.

Model information sources

· Weights licence ↗ · Parameter count ↗

Publisher parameter count; includes the served backbone, not just adapter size.

29.9±0.9#308 of 355 decision modelsfrom 64 benchmark results across 4 sources

$ how it compares

The decision models ranked either side of InternLM Intern-Decision Qwen3.5-0.8B, out of 357 with a score, then more from Shanghai AI Laboratory (InternLM).

#	model	score	where	RAM	released
308	Kev 0.8B r15 Jared Palmer	30±1	local	~4.6GB	2026-09-24
309	PICK-150M v5 lCREEl	30±1	model files		2026-10-18
310	InternLM Intern-Decision Qwen3.5-0.8B Shanghai AI Laboratory (InternLM)	30±1	model files
311	OpenDecision (DecisionBench a51e07b5) deepanwadhwa	30±2	model files
312	Crivo-68M tardellirs	30±1	model files
	more from Shanghai AI Laboratory (InternLM)
222	InternLM Intern-Decision Qwen3.5-4B Shanghai AI Laboratory (InternLM)	48±1	model files
280	InternLM Intern-Decision Qwen3.5-2B Shanghai AI Laboratory (InternLM)	37±1	model files

see all decision models · find the ones that fit your machine

$ what it's good at

tools & automation▁▃▁▁▃▂▃▄▆██▆ #221 of 250 · 7.7% of its score · 6 tests

Beats DM-JEPA 1.1, Kodiak v0.2 1B (accuracy), JEV FLAN-T5 Large public v2 (342M) here, though they rank higher overall. Trails Prumo (rule-based engine), JevK5 Lite, Crivo-32M v2 here, though they rank lower overall.

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: BFCL (case exact accuracy) submitted	64.5% ✎	▁▂▁▃▁▂▂▄▅▆█▁ beats 28/246	very easy · avg 92%	▇▇ 4.7%	sharp · at its level · noisy
Decision Index 0.4.1: API-Bank (accuracy) submitted	21.1% ✎	▁▁▁▁▁▁▃▂▃▂█▂ beats 18/236	easy · avg 70%	▇ 1.6%	sharp · at its level · noisy
Decision Index 0.4.1: When2Call (accuracy) submitted	46.1% ✎	▁▁▁▂▃▅▅▆█▇█▃ beats 35/246	easy · avg 72%	▇ 0.8%	at its level · noisy
Decision Index 0.4.1: ToolRet (nDCG@10) submitted	47.4% ✎	▁▁▁▁▁·▁▃▁▄█▁ beats 25/246	medium · avg 60%	▇ 0.6%	blunt · at its level
Decision Index 0.4.1: Home appliance simulator (case exact accuracy) submitted	0.0% ✎	█▁▁▃▄▄▆▄▁▂▁▃ beats 36/243	medium · avg 37%	▇ 0.1%	sharp · too hard for it · noisy
Decision Index 0.4.1: RouterBench (selected quality (quality objective)) submitted	56.6% ✎	no other model yet		—	failed run: Publisher excludes this protocol because its prompt reveals GPT-4 as the best route. Evidence: https://huggingface.co/spaces/multimodalart/jev-decision-index/blob/c130faf65f82e81d3bdefb01e758c712dc5c5199/data/index.json

retrieval & classification▁▁▁·▁▃▁▁▃▃█▅ #243 of 258 · 3.6% of its score · 7 tests

Beats DM-JEPA 1.1, Together Tev1 Qwen3.5-0.8B here, though they rank higher overall. Trails Laya, Prumo (rule-based engine), MoganAI Lavoir ModernBERT-large here, though they rank lower overall.

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: Amazon ESCI (macro-F1) submitted	24.4% ✎	▁▁▁▁▁▁▃▂▃▃█▅ beats 16/246	medium · avg 47%	▇ 1.0%	at its level
Decision Index 0.4.1: BRIGHT (nDCG@10) submitted	22.4% ✎	▁▁▁▁▁▃▁▂▂▄▇█ beats 24/246	medium · avg 38%	▇ 1.0%	blunt · at its level
Decision Index 0.4.1: CLINC150+OOS (macro-F1) submitted	4.9% ✎	▁▁▁▃▁▁▁▂▃▆█▄ beats 7/238	easy · avg 83%	▇ 0.5%	sharp · at its level · noisy
Decision Index 0.4.1: HoVer (accuracy) submitted	52.3% ✎	▆▆▇▅▄▄▃▇▄█▆▄ beats 16/246	easy · avg 74%	▇ 0.4%	blunt · at its level
Decision Index 0.4.1: PhishNChips phishing decisions (accuracy) submitted	45.9% ✎	█▅▅▄▃▂▁▁▁▁·▁ beats 2/245	easy · avg 70%	▇ 0.4%	at its level · noisy
Decision Index 0.4.1: BANKING77 (macro-F1) submitted	11.8% ✎	▁·▁▁▃▁▁▁▂█▇█ beats 5/238	easy · avg 79%	▇ 0.3%	at its level · noisy
Decision Index 0.4.1: SGD/SGD-X (macro-F1) submitted	57.4% ✎	no other model yet		—	failed run: Publisher reports a builder bug exposing dialogue turns after the classified turn; awaiting corrected rerun. Evidence: https://huggingface.co/spaces/multimodalart/jev-decision-index/blob/c130faf65f82e81d3bdefb01e758c712dc5c5199/data/index.json

language understanding▂▃▂▃▂▅▆▃█▆▄▃ #232 of 256 · 18% of its score · 9 tests

Beats Kev 0.8B r15 here, though they rank higher overall. Trails JevK5 Lite, LFM2.5-2.6B-RLCD, JEV Ettin 400M here, though they rank lower overall.

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: HellaSwag (accuracy) submitted	43.6% ✎	▂▄▂▂▄▇▃▇█▅▃▁ beats 24/246	very easy · avg 85%	▇▇▇ 7.6%	sharp · at its level
Decision Index 0.4.1: NLI4CT (macro-F1) submitted	57.6% ✎	▁▁▁▂▂▃▃▄▇▇█▄ beats 36/246	easy · avg 74%	▇▇ 4.1%	at its level
Decision Index 0.4.1: ANLI (macro-F1) submitted	34.1% ✎	▁▂▃▅▅█▂····▁ beats 22/246	medium · avg 60%	▇ 2.9%	at its level
Decision Index 0.4.1: iSarcasmEval (Sarcasm F1 · track A, English) submitted	26.3% ✎	▁·▁·▁▁▂▄▅█▇▄ beats 42/246	medium · avg 44%	▇ 0.9%	typical
Decision Index 0.4.1: ContractNLI (macro-F1) submitted	35.4% ✎	▁▁▁▁▁▃▁▂▂▇▇█ beats 22/246	easy · avg 71%	▇ 0.8%	at its level · noisy
Decision Index 0.4.1: FinEntity (macro-F1) submitted	57.1% ✎	▁···▁▁▁▃▃▆█▃ beats 18/246	easy · avg 84%	▇ 0.7%	at its level · noisy
Decision Index 0.4.1: VAST (macro-F1) submitted	28.0% ✎	▁▁▃▂▅▄▄▂▄▆█▄ beats 7/246	medium · avg 62%	▇ 0.6%	at its level
Decision Index 0.4.1: RAGTruth (F1 on hallucinated class) submitted	53.3% ✎	▁▁▁▁▁▁▁▁▁▃▆█ beats 62/246	easy · avg 66%	▇ 0.5%	at its level · noisy

1 more test

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: ACOS (per-review F1) submitted	4.6% ✎	▁··▂▃▃▅▇█▇▃▃ beats 23/246	hard · avg 22%	▇ 0.3%	noisy

arts & human taste▁▇▄▃▅▅█▅▄▂▁▁ #228 of 247 · 5.6% of its score · 6 tests

Beats JEV Ettin 150M, JPT-0.8B Qwen3.5-0.8B LoRA, Sifr 0.8B v3.1 here, though they rank higher overall. Trails LFM2.5-350M-RLCD, system-one-gemma, Bekko System One v0 17M here, though they rank lower overall.

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: New Yorker (accuracy) submitted	27.1% ✎	▁▃▂▃▃▃▇▅█▅▃▁ beats 13/246	medium · avg 61%	▇ 2.3%	at its level
Decision Index 0.4.1: BPoMP (accuracy) submitted	50.4% ✎	▁█▄▄▅█▆▅▄▁▁▁ beats 19/246	easy · avg 83%	▇ 1.4%	sharp · at its level · noisy
Decision Index 0.4.1: Humicroedit (accuracy) submitted	53.7% ✎	▁·▁▃▃▂▅█▄▂▁▁ beats 47/246	medium · avg 60%	▇ 1.1%	blunt · at its level
Decision Index 0.4.1: cfcolor (accuracy) submitted	56.7% ✎	▁········▁▇█ beats 66/246	medium · avg 60%	▇ 0.6%	blunt · at its level
Decision Index 0.4.1: Habermas Machine (accuracy) submitted	44.6% ✎	▁▂▄█▇▅▁▁▄▄▁▁ beats 128/246	medium · avg 47%	▇ 0.2%	blunt · at its level
Decision Index 0.4.1: POP909-CL (accuracy) submitted	1.6% ✎	▄▅▅▃▆▅▃▅▂▅▃█ beats 34/237	hard · avg 21%	▇ 0.1%	sharp · too hard for it · noisy

knowledge & reasoning▁▂▂▃▂▃▃▅▅▆█▂ #218 of 263 · 38% of its score · 14 tests

Beats vLLM-SR vela3-fast (Vela 3.0, 0.4B), Decision-1.0-Eos-0.8B (DecisionBench 3c2d6326), Amber 0.4B here, though they rank higher overall. Trails laya (DecisionBench 1c5edc17), LFM2.5-2.6B-RLCD here, though they rank lower overall.

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: ARC-Easy (accuracy) submitted	81.2% ✎	▁▁▂▁▃▂▂▂▃▆█▅ beats 44/246	very easy · avg 96%	▇▇▇▇ 9.4%	sharp · at its level · noisy
Decision Index 0.4.1: ARC-Challenge (accuracy) submitted	62.9% ✎	▂▂▂▃▂▂▁▃▄▆█▆ beats 44/246	very easy · avg 90%	▇▇▇ 8.3%	sharp · at its level
Decision Index 0.4.1: MMLU (accuracy) submitted	46.9% ✎	▁▄▄▃▃▂▅▇▅█▇▁ beats 48/246	easy · avg 70%	▇▇ 5.0%	sharp · at its level
Decision Index 0.4.1: BBH (accuracy) submitted	42.7% ✎	▄▆▄▄█▇▇▄▃▁▁▁ beats 43/246	easy · avg 66%	▇▇ 4.0%	at its level
Decision Index 0.4.1: MMLU-Pro (accuracy) submitted	26.5% ✎	▄▄▃▃▂▄▅▇██▅▁ beats 56/246	medium · avg 46%	▇ 3.6%	sharp
Decision Index 0.4.1: WinoGrande (accuracy) submitted	53.1% ✎	█▅█▅▄█▆▄▃▃▁▁ beats 25/246	easy · avg 78%	▇ 2.8%	at its level
Decision Index 0.4.1: GPQA Diamond (accuracy) submitted	28.1% ✎	▂▆▅▅▆█▆▃▁··▁ beats 47/246	medium · avg 39%	▇ 1.3%	blunt · at its level
Decision Index 0.4.1: GSM8K (accuracy (4- and 10-choice)) submitted	18.6% ✎	▁··▄█▆▆▆▅▅▃▁ beats 21/246	medium · avg 45%	▇ 1.1%	sharp

6 more tests

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: MuSR (accuracy) submitted	51.3% ✎	▁▁▃█▅▄▁▁▁▁▁▁ beats 40/246	medium · avg 60%	▇ 0.7%	blunt · at its level
Decision Index 0.4.1: CLadder (accuracy) submitted	50.5% ✎	▁███▆▅▃▃▁▁▁▁ beats 17/246	easy · avg 71%	▇ 0.7%	at its level
Decision Index 0.4.1: CRUXEval (accuracy) submitted	32.8% ✎	██▄▃▃▄▁▁···▁ beats 11/246	medium · avg 58%	▇ 0.6%	at its level · noisy
Decision Index 0.4.1: SATA-Bench (case exact accuracy) submitted	3.4% ✎	▁▁▁▁▃▁▁▂▅█▂▁ beats 27/246	hard · avg 22%	▇ 0.4%	typical
Decision Index 0.4.1: ChessBench (accuracy) submitted	8.8% ✎	▄▇▄▄▄▆▄█▄▁▁▁ beats 42/246	hard · avg 16%	▇ 0.2%	blunt
Decision Index 0.4.1: HLE (accuracy) submitted	13.6% ✎	▁▁▂▃▆█▇▅▅▃▁▁ beats 164/246	very hard · avg 13%	▇ 0.0%	blunt

vision▃·▃▂▃▃▇▄▄█▄▃ #78 of 79 · 7.6% of its score · 13 tests

Beats vLLM-SR d3-edge (0.6B) here, though they rank higher overall. Trails LiquidAI d1-omni-600M here, though they rank lower overall.

test	result	vs the others in its run	difficulty	counts	why
JevalKit: VisualDecisionBench images	66.4% ✎	▄▄···█▄·█▄█▄ beats 0/10	easy · avg 78%	▇ 1.1%	blunt · at its level
Decision Index Vision 0.4 · Mind2Web (chance-corrected points) submitted	21.2100 points ✎	▃·▁▁▃▁▄▄▃▅█▂ beats 0/61	avg 63.423 points	▇ 0.8%	blunt
Decision Index Vision 0.4 · MMMU-Pro vision (chance-corrected points) submitted	7.6500 points ✎	▁▁▅▁▄▁▄█▄▃▇▇ beats 4/61	avg 22.797 points	▇ 0.8%	blunt
Decision Index Vision 0.4 · Winoground (chance-corrected points) submitted	43.7500 points ✎	▁·▁▃▁▁·▂▁▃▅█ beats 3/61	avg 66.987 points	▇ 0.7%	blunt
Decision Index Vision 0.4: private same skills (points)	33.7100 points ✎	▁▃▃▃▁▂▄▆▃▃▅█ beats 1/61	avg 48.067 points	▇ 0.7%	blunt
Decision Index Vision 0.4 · Moderation (Hateful Memes) (chance-corrected points) submitted	12.4500 points ✎	▆▃▃▆▄▄▇██▁▆▆ beats 3/61	avg 28.443 points	▇ 0.6%	blunt
Decision Index Vision 0.4 · RealWorldQA (chance-corrected points) submitted	38.1300 points ✎	▁·▃▂▁▃▃▅▅▃▂█ beats 3/61	avg 53.651 points	▇ 0.6%	blunt
Decision Index Vision 0.4 · CharXiv (chance-corrected points) submitted	48.3700 points ✎	▂▁▁▃▁▃▁▅▅▆██ beats 5/61	avg 62.137 points	▇ 0.5%	blunt

5 more tests

test	result	vs the others in its run	difficulty	counts	why
Decision Index Vision 0.4 · InfographicVQA (chance-corrected points) submitted	71.5800 points ✎	▁·▃▂▁▁▃▁▂▂▅█ beats 3/61	avg 83.859 points	▇ 0.4%	blunt
Decision Index Vision 0.4 · R-Bench-M (chance-corrected points) submitted	5.7900 points ✎	▃▄▇▆█▄▄▇▂··▁ beats 0/61	avg 19.676 points	▇ 0.4%	blunt
Decision Index Vision 0.4 · BLINK (chance-corrected points) submitted	24.9300 points ✎	▁···▃▂▂▂█▄▂▃ beats 3/61	avg 44.994 points	▇ 0.4%	blunt
Decision Index Vision 0.4 · CV-Bench (chance-corrected points) submitted	51.6700 points ✎	▃▁▁▁▂▁▁▁▄█▃▃ beats 2/61	avg 67.662 points	▇ 0.3%	blunt
Decision Index Vision 0.4 · KIE (CORD+FUNSD) (chance-corrected points) submitted	63.0000 points ✎	▃··▁▁▁▁▁▂▄█▁ beats 1/61	avg 85.184 points	▇ 0.2%	blunt

workflows▁▁▁▂▁▂▃▆█▄▁▁ #83 of 114 · 10% of its score · 6 tests

Beats Qwen3-Reranker-4B (DecisionBench 22e68366), Decision-1.0-Eos-0.8B (DecisionBench 3c2d6326), kev-0.6b (DecisionBench dece6dba) here, though they rank higher overall. Trails LiquidAI d1-omni-600M here, though they rank lower overall.

test	result	vs the others in its run	difficulty	counts	why
JevalKit: Procedural Typed Decisions	42.8% ✎	█·███▄·▄▄▄·▄ beats 0/12	easy · avg 67%	▇▇ 3.9%	sharp · at its level
Privacy policy · diagnostic43	27.9% ✎	█········▄·▄ beats 0/3	easy · avg 70%	▇ 2.3%	sharp · at its level
JevalKit: DecisionBench standard eval	49.0% ✎	▃▃·▃···▅█▅·█ beats 0/12	easy · avg 70%	▇ 1.8%	at its level
JevalKit: JevBench public 231	71.0% ✎	█▄▄▄▄▄██▄··▄ beats 0/12	easy · avg 82%	▇ 1.3%	at its level
Privacy policy · challenge56	96.4% ✎	▄·······▄··█ beats 1/3	very easy · avg 97%	▇ 0.8%	sharp · at its level · noisy
JevalKit: Typed Decisions held-out modal labels	77.7% ✎	▃▅··▃·▃▃·█▃█ beats 6/12	easy · avg 74%	▇ 0.1%	blunt · at its level

other tests5 not in a task · 8.5% of its score

test	result	vs the others in its run	difficulty	counts	why
JevalKit: JevAlt-Bench EN/TR/DE	77.5% ✎	▅··▃▃▅▃█··▅▃ beats 0/12	very easy · avg 87%	▇ 3.3%	typical
Decision Index 0.4.1: private same skills (equated points)	12.0300 points ✎	▂▂▃▃▃▃▄▅▅▇█▃ beats 20/247	avg 41.206 points	▇ 2.8%	blunt
Decision Index 0.4.1: private new domains (equated points)	13.7300 points ✎	▃█▃▃▂▆▃▃▄▄▄▄ beats 48/247	avg 38.861 points	▇ 1.6%	blunt
JevalKit: Decision Index public 0.3 (official weighted points)	8.4100 points ✎	▃▃·▃·▃▃▃▅▅·█ beats 0/12	avg 39.649 points	▇ 0.7%	blunt
JevalKit: Chinese decision validation v0.2	89.9% ✎	▃····█·█▃▃█▃ beats 8/12	very easy · avg 88%	▇ 0.1%	blunt

$ where to run it

Download model files ↗
Published model files verified. This is a verified repository snapshot; the benchmark does not establish an identical weight revision. A local run command and hardware requirements have not been verified for this entry. Source · checked 2026-10-31.

Model repository and documentation: huggingface.co/internlm ↗

$ how the score was worked out · Decision Index 0.4.1 78%, JevalKit (Valen Team) 12%, Decision Index Vision 0.4 6% and 1 more

Each result implies a score on its own, after adjusting for how hard its test is and who ran it. The score is their weighted average, with a small pull toward the middle for thinly tested models. Each test's weight is its counts column above; here it's added up by who ran the tests. How it works

source	results	share of the score	licence
Decision Index 0.4.1 · submitted; independent execution unverified	42	▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 78%	CC BY 4.0
JevalKit (Valen Team)	8	▇▇▇▇ 12%	Apache-2.0
Decision Index Vision 0.4 · submitted; independent execution unverified	12	▇▇ 6%	CC BY 4.0
FloorIsAwake · Privacy Decision Benchmark	2	▇ 3%	MIT
prior · pull toward the middle		▇ 0%
weighted average		= 29.9

not counted (2)

Decision Index 0.4.1	Decision Index 0.4.1: RouterBench (selected quality (quality objective)) [correct]	56.6%	failed run: Publisher excludes this protocol because its prompt reveals GPT-4 as the best route. Evidence: https://huggingface.co/spaces/multimodalart/jev-decision-index/blob/c130faf65f82e81d3bdefb01e758c712dc5c5199/data/index.json
Decision Index 0.4.1	Decision Index 0.4.1: SGD/SGD-X (macro-F1) [correct]	57.4%	failed run: Publisher reports a builder bug exposing dialogue turns after the classified turn; awaiting corrected rerun. Evidence: https://huggingface.co/spaces/multimodalart/jev-decision-index/blob/c130faf65f82e81d3bdefb01e758c712dc5c5199/data/index.json

$ improve this page

Update model information Add a place to run it Add a test result Propose a benchmark Correct a benchmark score Edit data on GitHub

Use a short GitHub form or edit the data through a pull request. Every number needs a source; here's which ones we can use.

data updated 2026-11-03 02:37 UTC · sources and licences · json