Ling 3.1 Flash vs Nemotron 3.5 Bolt 74B-A9B BF16

Updated October 16, 2026. We do not rank this pair: at least one has no public score. Public scores include evidence status and uncertainty.

Decision reading

At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner. 4 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

Model A

Ling 3.1 Flash

InclusionAI

68.02/100

Estimated · Public rank #25

Conditional range 53.7–82.4

Model B

Nemotron 3.5 Bolt 74B-A9B BF16

NVIDIA

—

Evidence status unavailable

90% interval unavailable

Shared results: 4
Ling 3.1 Flash only: 13
Nemotron 3.5 Bolt 74B-A9B BF16 only: 4
Like-for-like categories: 0 / 8

Estimated: Ling 3.1 Flash. Conditional ranges do not establish rank confidence.How the comparison works

Which one for your work

Recommendations appear only when a shared evidence basis or an explicit operating constraint supports the call. Secondary and unsupported use cases stay disclosed below the initial list.

Long documents
Prompts that approach the documented context limit
Ling 3.1 Flash
Ling 3.1 Flash has the larger documented context window.
Confidence: documented

Show secondary and unsupported calls

Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
Nemotron 3.5 Bolt 74B-A9B BF16 is not ranked on the public lane for coding, so no winner is named for coding.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
Nemotron 3.5 Bolt 74B-A9B BF16 is not ranked on the public lane for agentic, so no winner is named for agentic.
Confidence: limited
Chat turn cost
1K fresh input + 500 output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates
Cache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates
Repository review cost
50K fresh input + 3K output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates

Which one for a specific job

Choose a job from the LLM Selector's task catalog to see the category row it rests on, under the same basis rules as the table below. A directional row stays directional; choosing a job never creates a winner.

Pick the job you would use them for

The same task catalog as the LLM Selector. Each job names the evidence surface it rests on; nothing here adds a new score.

57.2Ling 3.1 Flash—Nemotron 3.5 Bolt 74B-A9B BF16

Not comparable · BenchAlign v5.8

The coding row is not comparable on the public lane: at least one model is not measured or not ranked there.

Coding scores combine specific tasks and setups. Match the editor, harness, and effort to your workflow.

Open the coding leaderboard Shortlist models for this job

Same basis rules as the category table below

Shape of the matched evidence

Only shared public evidence is shown. Sparse evidence stays a ruled list rather than being closed into a radar shape.

Too few matched category axes support a radar. The ruled list below shows only shared benchmark results; positions use each benchmark’s normalized display scale when available.

BrowseCompAgentic
Normalized gap 21.7
Ling 3.1 Flash:91.7%
Nemotron 3.5 Bolt 74B-A9B BF16:70%
Ling 3.1 Flash source Nemotron 3.5 Bolt 74B-A9B BF16 source

Bars run 0–100 on each benchmark’s normalized display scale

Category results, on a stated basis

Each row shows the public-lane category score for both models: the BenchAlign v5.8 lane for agentic, coding, and knowledge, and the weighted public rows elsewhere, with the same rank each model page reports. A row is like-for-like only when both scores rest on Supported evidence or the same weighted set. Directional and not-comparable rows remain visible, but they never receive a winner.

Agentic

Not comparable

Ling 3.1 Flash: 62.7; Estimated · #22/128
Nemotron 3.5 Bolt 74B-A9B BF16: Not ranked
Basis: BenchAlign v5.8 lane · 10 vs 6 public rows
Reading: Not comparable

Coding

Not comparable

Ling 3.1 Flash: 57.2; Estimated · #26/150
Nemotron 3.5 Bolt 74B-A9B BF16: Not ranked
Basis: BenchAlign v5.8 lane · 5 vs 0 public rows
Reading: Not comparable

Reasoning

Not comparable

Ling 3.1 Flash: 82.9; Unranked · 2 rankable rows
Nemotron 3.5 Bolt 74B-A9B BF16: 72.1; Unranked · 1 rankable row
Basis: Provisional lane · 0 vs 0 weighted rows
Reading: Not comparable

Multimodal

Not comparable

Ling 3.1 Flash: Not ranked
Nemotron 3.5 Bolt 74B-A9B BF16: Not ranked
Basis: Provisional lane · 0 vs 0 weighted rows
Reading: Not comparable

Knowledge

Not comparable

Ling 3.1 Flash: 63.3; Supported · #42/184
Nemotron 3.5 Bolt 74B-A9B BF16: Not ranked
Basis: BenchAlign v5.8 lane · 2 vs 2 public rows
Reading: Not comparable

Multilingual

Not comparable

Ling 3.1 Flash: Not ranked
Nemotron 3.5 Bolt 74B-A9B BF16: Not ranked
Basis: Provisional lane · 0 vs 0 weighted rows
Reading: Not comparable

Instruction following

Not comparable

Ling 3.1 Flash: Not ranked
Nemotron 3.5 Bolt 74B-A9B BF16: Not ranked
Basis: Provisional lane · 0 vs 0 weighted rows
Reading: Not comparable

Math

Not comparable

Ling 3.1 Flash: Not ranked
Nemotron 3.5 Bolt 74B-A9B BF16: Not ranked
Basis: Provisional lane · 0 vs 0 weighted rows
Reading: Not comparable

Category scores with the server-provided evidence basis for Ling 3.1 Flash and Nemotron 3.5 Bolt 74B-A9B BF16
Category	Ling 3.1 Flash	Nemotron 3.5 Bolt 74B-A9B BF16	Basis	Reading
Agentic	62.7Estimated · #22/128	Not ranked	Not comparableBenchAlign v5.8 lane · 10 vs 6 public rows	Not comparable
Coding	57.2Estimated · #26/150	Not ranked	Not comparableBenchAlign v5.8 lane · 5 vs 0 public rows	Not comparable
Reasoning	82.9Unranked · 2 rankable rows	72.1Unranked · 1 rankable row	Not comparableProvisional lane · 0 vs 0 weighted rows	Not comparable
Multimodal	Not ranked	Not ranked	Not comparableProvisional lane · 0 vs 0 weighted rows	Not comparable
Knowledge	63.3Supported · #42/184	Not ranked	Not comparableBenchAlign v5.8 lane · 2 vs 2 public rows	Not comparable
Multilingual	Not ranked	Not ranked	Not comparableProvisional lane · 0 vs 0 weighted rows	Not comparable
Instruction following	Not ranked	Not ranked	Not comparableProvisional lane · 0 vs 0 weighted rows	Not comparable
Math	Not ranked	Not ranked	Not comparableProvisional lane · 0 vs 0 weighted rows	Not comparable

Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign v5.8) differ from the provisional-lane categories. Unranked scores sit on the provisional lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.

Supported evidence per lane · bars run 0–100Methodology

What each workload costs

Three fixed token mixes turn per-token rates into comparable decisions. Each scenario states context fit and whether cached input had to fall back to the published list-input rate.

Chat turn

1K fresh input + 500 output tokens

Ling 3.1 Flash: API rate not published; Fits in one request
Nemotron 3.5 Bolt 74B-A9B BF16: API rate not published; Fits in one request

Ling 3.1 Flash has no comparable published API token rate. Nemotron 3.5 Bolt 74B-A9B BF16 has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

Ling 3.1 Flash: API rate not published; Fits in one request
Nemotron 3.5 Bolt 74B-A9B BF16: API rate not published; Fits in one request

Ling 3.1 Flash has no comparable published API token rate. Nemotron 3.5 Bolt 74B-A9B BF16 has no comparable published API token rate.

Cache-heavy agent loop

200K cached + 20K fresh input + 10K output tokens

Ling 3.1 Flash: API rate not published; Fits in one request; Cached-input rate unavailable
Nemotron 3.5 Bolt 74B-A9B BF16: API rate not published; Fits in one request; Cached-input rate unavailable

Ling 3.1 Flash has no comparable published API token rate. Nemotron 3.5 Bolt 74B-A9B BF16 has no comparable published API token rate.

Cached input falls back to the list input rate only where a cached rate is unpublished

Specification differences

Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.

SpecificationLing 3.1 FlashNemotron 3.5 Bolt 74B-A9B BF16

Context window

Maximum documented context; output-token limits may be lower.

Ling 3.1 Flash

262K

InclusionAI Ling 3.1 Flash released configuration

Nemotron 3.5 Bolt 74B-A9B BF16

256K

NVIDIA BF16 model card

API model ID

Ling 3.1 Flash

inclusionai/ling-3.1-flash

Vercel AI Gateway Ling 3.1 Flash route

Nemotron 3.5 Bolt 74B-A9B BF16

Not sourced

Cached-input rate

A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.

Ling 3.1 Flash

No comparable hosted API rate

Vercel AI Gateway availability

Nemotron 3.5 Bolt 74B-A9B BF16

No comparable hosted API rate

NVIDIA Hugging Face model card

Documented inputs

Ling 3.1 Flash

text

InclusionAI Ling 3.1 Flash model card

Nemotron 3.5 Bolt 74B-A9B BF16

text, image, video

NVIDIA BF16 model card

Documented outputs

Ling 3.1 Flash

text

InclusionAI Ling 3.1 Flash model card

Nemotron 3.5 Bolt 74B-A9B BF16

text

NVIDIA BF16 model card

Provider availability

Ling 3.1 Flash

Generally Available · Hugging Face weights, SGLang, vLLM, Vercel AI Gateway API via Novita

Vercel AI Gateway Ling 3.1 Flash route

Nemotron 3.5 Bolt 74B-A9B BF16

Open Weights · Hugging Face, self-hosted inference

NVIDIA BF16 model card

Reasoning profile

Ling 3.1 Flash

Reasoning

Nemotron 3.5 Bolt 74B-A9B BF16

Reasoning

Weight access

Ling 3.1 Flash

Open Weight

Nemotron 3.5 Bolt 74B-A9B BF16

Open Weight

License

Ling 3.1 Flash

Open Weight

Nemotron 3.5 Bolt 74B-A9B BF16

Open Weight

Release date

Ling 3.1 Flash

2026-09-29

Nemotron 3.5 Bolt 74B-A9B BF16

2026-10-15

If you already use one of these models

Deployment change: The models list different providers, so authentication, endpoint behavior, limits, and feature support may change.
Quality signal: At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.
Workload cost: A complete comparable API-rate estimate is not available for both models.
Context tradeoff: Ling 3.1 Flash has the larger documented window (262K).

Run the same representative tasks against both endpoints before changing production traffic.

Questions

Which is better, Ling 3.1 Flash or Nemotron 3.5 Bolt 74B-A9B BF16?

At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner. The page therefore keeps the decision tied to the specific documented workload.

Which is better for coding, Ling 3.1 Flash or Nemotron 3.5 Bolt 74B-A9B BF16?

Nemotron 3.5 Bolt 74B-A9B BF16 is not ranked on the public lane for coding, so no winner is named for coding.

Which is better for agentic tasks, Ling 3.1 Flash or Nemotron 3.5 Bolt 74B-A9B BF16?

Nemotron 3.5 Bolt 74B-A9B BF16 is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.

Which costs less, Ling 3.1 Flash or Nemotron 3.5 Bolt 74B-A9B BF16?

Both models do not have comparable published API token rates, so this page does not name a universal price winner.

Which has the larger context window, Ling 3.1 Flash or Nemotron 3.5 Bolt 74B-A9B BF16?

Ling 3.1 Flash has the larger documented context window: 262K, compared with 256K.

Self-host vs API cost

Estimates at 50,000 req/day · 1000 tokens/req average.

Ling 3.1 Flash

API / mo$0

Self-host / mo$27,962

Break-even—

Nemotron 3.5 Bolt 74B-A9B BF16

API / mo$0

Self-host / moNot listed

Break-even—

Proprietary model — self-hosting not applicable.

Model the full break-even

Benchmark evidence

The full public result ledger is available for audit without forcing a wide desktop table onto a phone.

Browse raw public benchmark evidence21 rows

Agentic

skillsBench
Ling 3.1 Flash68.7%
Source
Nemotron 3.5 Bolt 74B-A9B BF16—
Not directly comparable
AutomationBench
Ling 3.1 Flash52.5%
Source
Nemotron 3.5 Bolt 74B-A9B BF16—
Not directly comparable
CyberGym
Ling 3.1 Flash87.9%
Source
Nemotron 3.5 Bolt 74B-A9B BF16—
Not directly comparable
Finance Agent v2
Ling 3.1 Flash57.9%
Source
Nemotron 3.5 Bolt 74B-A9B BF16—
Not directly comparable
DRACO
Ling 3.1 Flash85.5%
Source
Nemotron 3.5 Bolt 74B-A9B BF16—
Not directly comparable
Terminal-Bench 2.1
Ling 3.1 Flash81.2%
Source
Nemotron 3.5 Bolt 74B-A9B BF1653.9%
Source
Ling 3.1 Flash leads this result
τ³-bench results
Ling 3.1 Flash47.8%
Source
Nemotron 3.5 Bolt 74B-A9B BF1617.0%
Source
Ling 3.1 Flash leads this result
MCP Atlas
Ling 3.1 Flash83%
Source
Nemotron 3.5 Bolt 74B-A9B BF1655.6%
Source
Ling 3.1 Flash leads this result
BrowseComp
Ling 3.1 Flash91.7%
Source
Nemotron 3.5 Bolt 74B-A9B BF1670%
Source
Ling 3.1 Flash leads this result
WideResearch
Ling 3.1 Flash83.3%
Source
Nemotron 3.5 Bolt 74B-A9B BF16—
Not directly comparable
PinchBench
Ling 3.1 Flash—
Nemotron 3.5 Bolt 74B-A9B BF1690.3%
Source
Not directly comparable
WebArena
Ling 3.1 Flash—
Nemotron 3.5 Bolt 74B-A9B BF1650.3%
Source
Not directly comparable

Coding

terminalBench4
Ling 3.1 Flash46.0%
Source
Nemotron 3.5 Bolt 74B-A9B BF16—
Not directly comparable
SWE-Atlas Codebase QnA
Ling 3.1 Flash64.5%
Source
Nemotron 3.5 Bolt 74B-A9B BF16—
Not directly comparable
SWE Multilingual
Ling 3.1 Flash88.5%
Source
Nemotron 3.5 Bolt 74B-A9B BF16—
Not directly comparable
SWE-bench Pro
Ling 3.1 Flash68.7%
Source
Nemotron 3.5 Bolt 74B-A9B BF16—
Not directly comparable
DeepSWE
Ling 3.1 Flash59.7%
Source
Nemotron 3.5 Bolt 74B-A9B BF16—
Not directly comparable

Knowledge

HealthBench Professional
Ling 3.1 Flash65.3%
Source
Nemotron 3.5 Bolt 74B-A9B BF16—
Not directly comparable
HLE
Ling 3.1 Flash37.4%
Source
Nemotron 3.5 Bolt 74B-A9B BF16—
Not directly comparable
GPQA-D
Ling 3.1 Flash—
Nemotron 3.5 Bolt 74B-A9B BF1688.8%
Source
Not directly comparable
HLE w/o tools
Ling 3.1 Flash—
Nemotron 3.5 Bolt 74B-A9B BF1628.7%
Source
Not directly comparable

21 public results · 4 shared

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Last updated October 16, 2026

Ling 3.1 Flash vs Nemotron 3.5 Bolt 74B-A9B BF16

Decision reading

Which one for your work

Long documents

Coding work

Agentic work

Chat turn cost

Cache-heavy agent loop cost

Repository review cost

Which one for a specific job

What is actually comparable

Shape of the matched evidence

Category results, on a stated basis

Agentic

Coding

Reasoning

Multimodal

Knowledge

Multilingual

Instruction following

Math

What each workload costs

Chat turn

Repository review

Cache-heavy agent loop

Specification differences

Context window

API model ID

Cached-input rate

Documented inputs

Documented outputs

Provider availability

Reasoning profile

Weight access

License

Release date

If you already use one of these models

Questions

Which is better, Ling 3.1 Flash or Nemotron 3.5 Bolt 74B-A9B BF16?

Which is better for coding, Ling 3.1 Flash or Nemotron 3.5 Bolt 74B-A9B BF16?

Which is better for agentic tasks, Ling 3.1 Flash or Nemotron 3.5 Bolt 74B-A9B BF16?

Which costs less, Ling 3.1 Flash or Nemotron 3.5 Bolt 74B-A9B BF16?

Which has the larger context window, Ling 3.1 Flash or Nemotron 3.5 Bolt 74B-A9B BF16?

Self-host vs API cost

Benchmark evidence

Agentic

Coding

Knowledge

Related comparisons

Watch Ling 3.1 Flash vs Nemotron 3.5 Bolt 74B-A9B BF16