Cheapest LLM for SEC Filings 2026

The cheapest LLM for SEC filings in 2026 that still fits a full 10-K in context is Gemini 2.5 Flash at $0.30 / $2.50 per Mtok: about $0.046 to read a 120k-token filing and emit a 4k-token extraction, with a 1M-token window that swallows the largest filings whole. DeepSeek V4-Flash has a 1M window too but is no longer the floor: its peak rates are $0.44 / $1.32 (~$0.058/filing), halving off-peak to ~$0.029. GPT-5.4-nano is the cheapest fitted option at ~$0.029/filing. Verified list prices below. The deciding axis is not the headline rate but context fit and the accuracy floor your extraction needs. Model the per-filing cost with the Token Cost Optimizer.

TL;DR

Per-filing costs are computed from the verified list prices (120,000 input tokens × input rate + 4,000 output tokens × output rate), not from a benchmark run. All prices verified 2026-05-25 against each vendor's official pricing page.

Why context fit decides this, not the headline rate

A 10-K is large. The text body of a full annual report commonly lands in the ~100k–150k-token range, and complex filings push higher. If the model's context window cannot hold the filing, the cheap per-token rate is irrelevant: you are forced into chunking, retrieval, and stitching, which adds engineering cost and accuracy risk.

That immediately reshapes the budget shortlist:

• Claude Haiku 4.5 is cheap ($1/$5) but its 200k context window is the binding constraint for the largest filings: comfortable for most 10-Ks, tight for the biggest.¹
• Gemini 2.5 Flash carries a 1M-token window, so any single filing fits with room for instructions and few-shot examples.²
• DeepSeek V4-Flash also carries a 1M context window with 384k max output, making it the cheapest full-filing-fit option on a per-token basis.³
• GPT-5.4-nano / mini use tiered short/long-context pricing; verify your filing size against the tier boundary before relying on the short-context rate.⁴

The verified budget-tier prices

Gemini 2.5 Flash $0.30 / Mtok input, $2.50 / Mtok output, 1M context.²

Claude Haiku 4.5 $1 / Mtok input, $5 / Mtok output, 200k context; cache reads at 0.1x base input.¹

GPT-5.4-mini ($0.75 / Mtok input ($0.075 cached), $4.50 / Mtok output. GPT-5.4-nano) $0.20 / Mtok input ($0.02 cached), $1.25 / Mtok output.⁴

DeepSeek V4-Flash $0.44 / Mtok cache-miss input ($0.014 cache-hit), $1.32 / Mtok output, 1M context — peak rates, halved off-peak (peak is 01:00-04:00 and 06:00-10:00 UTC, Monday to Friday). Automatic context caching is on by default, so the boilerplate that repeats across filings can hit the cache-hit rate.³

Caching amortizes the filing boilerplate

Filings share enormous structural boilerplate: risk-factor headers, accounting-policy language, standard table layouts. If your prompt pins a fixed extraction schema and instruction block ahead of the filing-specific text, caching that prefix turns it nearly free after the first call. Anthropic cache reads are 0.1x base input; OpenAI cached input is a 90% discount; DeepSeek's cache-hit input is ~3% of the cache-miss rate ($0.014 vs $0.44).¹⁴³ Over a thousand-filing sweep, the cached prefix can shave a meaningful fraction off the bill.

The accuracy floor caveat

Cheaper does not mean adequate. A budget model that misreads a parenthetical "(loss)" as a positive number, or drops a footnote that reverses the headline figure, is not cheap: it is expensive in errors. The defensible workflow: pick the cheapest model that clears your extraction accuracy bar on your own filings, measured with an eval harness, not the cheapest model outright. For high-stakes numeric fields, a budget extractor feeding a frontier verifier (see Claude vs GPT-5 vs Gemini) often beats either alone.

Verified engine output

The block below runs the Token Cost Optimizer on a filing-extraction workload: Gemini 2.5 Flash, 120k input + 4k output per call, one call per filing, 50 filings/day, with a partial cache-hit assumption. It returns the per-call, per-validated, and monthly cost from the engine's own rate table. The output is computed live from the shipped bundle, not typed by hand.

Decision guidance

• Absolute cheapest, full-filing fit, hosted API GPT-5.4-nano (~$0.029/filing); DeepSeek V4-Flash (1M context) matches it only off-peak and is ~$0.058 at peak. Verify data-handling terms suit your use.
• Cheapest from a major US-frontier vendor with 1M context Gemini 2.5 Flash (~$0.046/filing).
• Need 90%+ extraction accuracy on hard numeric fields run an eval; a budget extractor + frontier verifier may be the real cheapest-correct path.
• Repeated schema/boilerplate across thousands of filings turn on caching; it changes the per-call math materially.

Connects to

• Token Cost Optimizer: per-filing cost from your own token shape.
• Cheapest SEC EDGAR API source: the free filing text these models read.
• Claude vs GPT-5 vs Gemini for Financial Analysis 2026: when the task needs a reasoning tier above budget.
• DeepSeek vs Mistral for Financial Analysis 2026: the open-weight budget corner in depth.

References

Footnotes

1. Anthropic. "Pricing." platform.claude.com, verified 2026-05-25. https://platform.claude.com/docs/en/about-claude/pricing ↩ ↩² ↩³

2. Google. "Gemini Developer API pricing." ai.google.dev, verified 2026-05-25. https://ai.google.dev/gemini-api/docs/pricing ↩ ↩²

3. DeepSeek. "Models & Pricing." api-docs.deepseek.com, verified 2026-05-25. https://api-docs.deepseek.com/quick_start/pricing ↩ ↩² ↩³

4. OpenAI. "API Pricing." developers.openai.com, verified 2026-05-25. https://developers.openai.com/api/docs/pricing ↩ ↩² ↩³

Verified engine output

Show the recompute-verified inputs and outputs

Inputs

model_id	gemini-2-5-flash
input_tokens_per_call	120000
output_tokens_per_call	4000
calls_per_idea	1
retry_rate	0.05
ideas_per_day	50
validation_rate	0.9
cache_hit_rate	0.6

Result

model › id	gemini-2-5-flash
model › provider	google
model › name	Gemini 2.5 Flash
model › input usd per mtoken	0.3
model › output usd per mtoken	2.5
model › context window	1000000
model › notes	Fast mid-tier; 1M context.
effective cost per call	0.046
cost per idea	0.0483
cost per validated trade	0.05366666666666667
cost per day	2.415
cost per month	72.45
cost per year	881.475

Computed live at build time.

Frequently asked questions

What is the cheapest LLM for processing SEC filings in 2026?

GPT-5.4-nano at about $0.029 per 120k-token filing. DeepSeek V4-Flash ($0.44/$1.32 peak, 1M context) matches that only in its off-peak window and costs ~$0.058 at peak, having tripled its rates in mid-2026. Among the 1M-context options from major US-frontier vendors, Gemini 2.5 Flash ($0.30/$2.50) is ~$0.046 per filing.

Which budget models fit a full 10-K in context?

Gemini 2.5 Flash and DeepSeek V4-Flash both carry 1M-token windows. Claude Haiku 4.5 has 200k, fine for most filings but tight for the largest. Verify GPT-5.4 nano/mini against their context-tier boundary.

Does caching make filing extraction cheaper?

Yes. Filings share heavy boilerplate; caching a fixed schema/instruction prefix costs about 10% of base input on Anthropic and Gemini, a 90% discount on OpenAI, and about 2% of cache-miss on DeepSeek.

Is the cheapest model good enough for filings?

Not automatically. A budget model that misreads a numeric field is expensive in errors. Pick the cheapest model that clears your accuracy bar on an eval of your own filings.

Where do these prices come from?

Each vendor's official pricing page, verified 2026-05-25. Per-filing costs are computed from those list prices, not a benchmark run.