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Ling 3.0 Flash Fin vs Phi-3.5-mini-instruct

Ling 3.0 Flash Fin leads the LLM Stats Score 43.3 to -3.8. Ling 3.0 Flash Fin is 1.1x cheaper per token.

InclusionAI · Microsoft · Updated for 2026

Which is better?

Ling 3.0 Flash Fin leads the overall LLM Stats Score 43.3 to -3.8, ranking #39 overall.

On price, Ling 3.0 Flash Fin is roughly 1.1x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

Ling 3.0 Flash Fin also accepts a larger context window (262,144 input tokens), making it the stronger choice for long documents and large codebases.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose Ling 3.0 Flash Fin

  • overall performance matters — it scores 43.3 and ranks #39 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • cost matters — it's about 1.1x cheaper per token
  • you process long inputs — it offers a 262,144 token context window
  • you want the most recent training data — it shipped Sep 2026

Choose Phi-3.5-mini-instruct

  • you need open weights you can self-host or fine-tune

At a glance

The differences that matter most.

Ling 3.0 Flash Fin
InclusionAI
Phi-3.5-mini-instruct
Microsoft
Core performance indexes
LLM Stats Score
43.3
#39
-3.8
#344
Reasoning
44.7
#32
-4.7
#340
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.06 / M
$0.10 / M
Output price
$0.18 / M
$0.10 / M
Context window
262,144
128,000

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
Ling 3.0 Flash Fin
Phi-3.5-mini-instruct
Finance
36.7#5
0.6#195
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

6 reported for Ling 3.0 Flash Fin · 31 for Phi-3.5-mini-instruct

No common benchmarks found

Ling 3.0 Flash Fin and Phi-3.5-mini-instructdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Human preference

Blind head-to-head votes and playground preference scores

Pricing Analysis

Price comparison per million tokens

Ling 3.0 Flash Fin costs less

For input processing, Ling 3.0 Flash Fin ($0.06/1M tokens) is 1.7x cheaper than Phi-3.5-mini-instruct ($0.10/1M tokens).

For output processing, Ling 3.0 Flash Fin ($0.18/1M tokens) is 1.8x more expensive than Phi-3.5-mini-instruct ($0.10/1M tokens).

In conclusion, Phi-3.5-mini-instruct is more expensive than Ling 3.0 Flash Fin.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Tue Sep 08 2026 • llm-stats.com
InclusionAI
Ling 3.0 Flash Fin
Input tokens$0.06
Output tokens$0.18
Best providerDeepinfra
Microsoft
Phi-3.5-mini-instruct
Input tokens$0.10
Output tokens$0.10
Best providerAzure
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

120.2B diff

Ling 3.0 Flash Fin has 120.2B more parameters than Phi-3.5-mini-instruct, making it 3163.2% larger.

InclusionAI
Ling 3.0 Flash Fin
124.0Bparameters
Microsoft
Phi-3.5-mini-instruct
3.8Bparameters
124.0B
Ling 3.0 Flash Fin
3.8B
Phi-3.5-mini-instruct

Context Window

Maximum input and output token capacity

Ling 3.0 Flash Fin accepts 262,144 input tokens compared to Phi-3.5-mini-instruct's 128,000 tokens. Ling 3.0 Flash Fin can generate longer responses up to 262,144 tokens, while Phi-3.5-mini-instruct is limited to 128,000 tokens.

InclusionAI
Ling 3.0 Flash Fin
Input262,144 tokens
Output262,144 tokens
Microsoft
Phi-3.5-mini-instruct
Input128,000 tokens
Output128,000 tokens
Tue Sep 08 2026 • llm-stats.com

Release Timeline

When each model was launched

Ling 3.0 Flash Fin was released on 2026-09-03, while Phi-3.5-mini-instruct was released on 2024-08-23.

Ling 3.0 Flash Fin is 25 months newer than Phi-3.5-mini-instruct.

Ling 3.0 Flash Fin

Sep 3, 2026

5 days ago

2.0yr newer
Phi-3.5-mini-instruct

Aug 23, 2024

2.0 years ago

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Provider Availability

Ling 3.0 Flash Fin is available from DeepInfra. Phi-3.5-mini-instruct is available from Azure.

Ling 3.0 Flash Fin

deepinfra logo
Deepinfra
Input Price:Input: $0.06/1MOutput Price:Output: $0.18/1M

Phi-3.5-mini-instruct

azure logo
Azure
Input Price:Input: $0.10/1MOutput Price:Output: $0.10/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against Ling 3.0 Flash Fin and Phi-3.5-mini-instruct side-by-side, then vote on the output you prefer.

Ling 3.0 Flash Fin
✓ Preferred
Phi-3.5-mini-instruct
Open in Playground

FAQ

Common questions about Ling 3.0 Flash Fin vs Phi-3.5-mini-instruct.

Which is better, Ling 3.0 Flash Fin or Phi-3.5-mini-instruct?

Ling 3.0 Flash Fin leads the LLM Stats Score 43.3 to -3.8. Ling 3.0 Flash Fin is made by InclusionAI and Phi-3.5-mini-instruct is made by Microsoft. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does Ling 3.0 Flash Fin compare to Phi-3.5-mini-instruct in benchmarks?

Ling 3.0 Flash Fin scores SpreadSheetBench-v1: 86.5%, Finance Agent v1.1: 69.2%, Finance Agent v2: 59.8%, Tau3 Banking: 41.0%, APEX-Agents: 29.2%. Phi-3.5-mini-instruct scores GSM8k: 86.2%, ARC-C: 84.6%, RULER: 84.1%, PIQA: 81.0%, OpenBookQA: 79.2%.

Is Ling 3.0 Flash Fin cheaper than Phi-3.5-mini-instruct?

Ling 3.0 Flash Fin is 1.7x cheaper for input tokens. Ling 3.0 Flash Fin costs $0.06/M input and $0.18/M output via deepinfra. Phi-3.5-mini-instruct costs $0.10/M input and $0.10/M output via azure.

What are the context window sizes for Ling 3.0 Flash Fin and Phi-3.5-mini-instruct?

Ling 3.0 Flash Fin supports 262K tokens and Phi-3.5-mini-instruct supports 128K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Ling 3.0 Flash Fin and Phi-3.5-mini-instruct?

Key differences include LLM Stats Score (43.3 vs -3.8), context window (262K vs 128K), input pricing ($0.06 vs $0.10/M), licensing (Unknown vs MIT). See the full comparison above for benchmark-by-benchmark results.

Who makes Ling 3.0 Flash Fin and Phi-3.5-mini-instruct?

Ling 3.0 Flash Fin is developed by InclusionAI and Phi-3.5-mini-instruct is developed by Microsoft.

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